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Added Strength Slider to virtual lora (WebUI extension) | 1 | 2025-01-03T20:07:11 | https://www.reddit.com/r/LocalLLaMA/comments/1hsvo3f/added_strength_slider_to_virtual_lora_webui/ | FPham | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hsvo3f | false | null | t3_1hsvo3f | /r/LocalLLaMA/comments/1hsvo3f/added_strength_slider_to_virtual_lora_webui/ | false | false | 1 | null |
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Added Strength to LORA in VirtualLora (WebUI extension) | 30 | 2025-01-03T20:08:08 | FPham | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1hsvow5 | false | null | t3_1hsvow5 | /r/LocalLLaMA/comments/1hsvow5/added_strength_to_lora_in_virtuallora_webui/ | false | false | default | 30 | {'enabled': True, 'images': [{'id': 'brqwcfbl5uae1', 'resolutions': [{'height': 34, 'url': 'https://preview.redd.it/brqwcfbl5uae1.jpeg?width=108&crop=smart&auto=webp&s=577125fe7a7107448d875a9a96f269e4fcb09b50', 'width': 108}, {'height': 69, 'url': 'https://preview.redd.it/brqwcfbl5uae1.jpeg?width=216&crop=smart&auto=webp&s=0f75981e538337cefd895ee5ee4ad9422e209337', 'width': 216}, {'height': 103, 'url': 'https://preview.redd.it/brqwcfbl5uae1.jpeg?width=320&crop=smart&auto=webp&s=9d400ba8975dfa63b894aafadeb82a97a8ba0e30', 'width': 320}, {'height': 206, 'url': 'https://preview.redd.it/brqwcfbl5uae1.jpeg?width=640&crop=smart&auto=webp&s=0f213fe360f0f1277c5863a22b07db4c777369f5', 'width': 640}], 'source': {'height': 304, 'url': 'https://preview.redd.it/brqwcfbl5uae1.jpeg?auto=webp&s=bb2be7a65b8554342457dda470c5cf69c7775573', 'width': 944}, 'variants': {}}]} |
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Percy's list of scientific breakthroughs | 1 | 2025-01-03T20:19:03 | https://docs.google.com/document/d/1Yrof6qlDp3cMBRYjsmajg2KlwtBChHeXmq-FeWePjw8/edit?usp=sharing | Radlib123 | docs.google.com | 1970-01-01T00:00:00 | 0 | {} | 1hsvy5j | false | null | t3_1hsvy5j | /r/LocalLLaMA/comments/1hsvy5j/percys_list_of_scientific_breakthroughs/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'DMlyIZYENA6v2CKRF8nTW04yWEjyJQKhVLERtvLSufo', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/GgzOkw1LaED4n3pUBnjA1lcabSLHg5yptw9QxpCSXHg.jpg?width=108&crop=smart&auto=webp&s=5ae140ff083aac4d5dd9edbdf3b23644a7ee5712', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/GgzOkw1LaED4n3pUBnjA1lcabSLHg5yptw9QxpCSXHg.jpg?width=216&crop=smart&auto=webp&s=c7722d25a0833f3b4639aefe879b5a4ca74286d6', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/GgzOkw1LaED4n3pUBnjA1lcabSLHg5yptw9QxpCSXHg.jpg?width=320&crop=smart&auto=webp&s=5c79a7bb6e04a559c5e0b6e3b76132e509b3da85', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/GgzOkw1LaED4n3pUBnjA1lcabSLHg5yptw9QxpCSXHg.jpg?width=640&crop=smart&auto=webp&s=ec8cad470895770f7482a2a40844f113463f1b7c', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/GgzOkw1LaED4n3pUBnjA1lcabSLHg5yptw9QxpCSXHg.jpg?width=960&crop=smart&auto=webp&s=67fd3c8786125477bfb03f2e85615ea2457faafa', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/GgzOkw1LaED4n3pUBnjA1lcabSLHg5yptw9QxpCSXHg.jpg?width=1080&crop=smart&auto=webp&s=769fed641a7d212b4be68ac0a2cb9471aada4d7c', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/GgzOkw1LaED4n3pUBnjA1lcabSLHg5yptw9QxpCSXHg.jpg?auto=webp&s=c7af4722a598444512a3bc30636699e0a0c9b3ce', 'width': 1200}, 'variants': {}}]} |
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Open-source implementation of NotebookLM in <50 lines of code! | 1 | [removed] | 2025-01-03T20:30:43 | https://www.reddit.com/r/LocalLLaMA/comments/1hsw7u6/opensource_implementation_of_notebooklm_in_50/ | Dart7989 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hsw7u6 | false | null | t3_1hsw7u6 | /r/LocalLLaMA/comments/1hsw7u6/opensource_implementation_of_notebooklm_in_50/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': '8ibZHSgIz0H3oiF50U88eY1qL6LVzHEX6Lbp4wGFOtY', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/MVoruBX9iZ7E_mW27AyaaS33U9aRThP4tiydcxO0cqs.jpg?width=108&crop=smart&auto=webp&s=ea6f945a031a6ad3eb2361ab6703fe7aecd3302a', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/MVoruBX9iZ7E_mW27AyaaS33U9aRThP4tiydcxO0cqs.jpg?width=216&crop=smart&auto=webp&s=e8cbf62c426f2f33a55ca904c53e24c630f23af4', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/MVoruBX9iZ7E_mW27AyaaS33U9aRThP4tiydcxO0cqs.jpg?width=320&crop=smart&auto=webp&s=b1987fb087fb4ecce4eacd0354e6303fab0dd95e', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/MVoruBX9iZ7E_mW27AyaaS33U9aRThP4tiydcxO0cqs.jpg?width=640&crop=smart&auto=webp&s=eb6345ec158aeb46af8ab9e92b0b06b46c3a3a9d', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/MVoruBX9iZ7E_mW27AyaaS33U9aRThP4tiydcxO0cqs.jpg?width=960&crop=smart&auto=webp&s=22bd48c513c40bf2597c304d9a23438b82e50fae', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/MVoruBX9iZ7E_mW27AyaaS33U9aRThP4tiydcxO0cqs.jpg?width=1080&crop=smart&auto=webp&s=34ede04200f890d8fc14687f967fd1f2da73103a', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/MVoruBX9iZ7E_mW27AyaaS33U9aRThP4tiydcxO0cqs.jpg?auto=webp&s=3fb45c3668abe86b0c022a1b49eda17022716905', 'width': 1200}, 'variants': {}}]} |
Open source platforms to load balance between models and provides | 1 | [removed] | 2025-01-03T20:36:28 | https://www.reddit.com/r/LocalLLaMA/comments/1hswcli/open_source_platforms_to_load_balance_between/ | topjakuqe | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hswcli | false | null | t3_1hswcli | /r/LocalLLaMA/comments/1hswcli/open_source_platforms_to_load_balance_between/ | false | false | self | 1 | null |
Package to group images based on content (using local models)? | 3 | Are there are any packages that can group images based on content? Like cat images, landscapes etc.? | 2025-01-03T21:01:54 | https://www.reddit.com/r/LocalLLaMA/comments/1hswxyj/package_to_group_images_based_on_content_using/ | rm-rf-rm | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hswxyj | false | null | t3_1hswxyj | /r/LocalLLaMA/comments/1hswxyj/package_to_group_images_based_on_content_using/ | false | false | self | 3 | null |
Need Help Building a Dual 3090 Setup with Optimal Cooling (Noise Doesn't Matter) | 1 | [removed] | 2025-01-03T21:02:18 | https://www.reddit.com/r/LocalLLaMA/comments/1hswyb3/need_help_building_a_dual_3090_setup_with_optimal/ | switchpizza | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hswyb3 | false | null | t3_1hswyb3 | /r/LocalLLaMA/comments/1hswyb3/need_help_building_a_dual_3090_setup_with_optimal/ | false | false | self | 1 | null |
What is the best cheapest or open source llm right now? | 0 | Plz I want to know this, ofcourse I know it can't be on the level of chatgpt. But even if it's on the level of a dumb human with 30 iq it will be fine. | 2025-01-03T21:02:49 | https://www.reddit.com/r/LocalLLaMA/comments/1hswyql/what_is_the_best_cheapest_or_open_source_llm/ | No_Macaroon_7608 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hswyql | false | null | t3_1hswyql | /r/LocalLLaMA/comments/1hswyql/what_is_the_best_cheapest_or_open_source_llm/ | false | false | self | 0 | null |
Is there any paper/topology/research about LLM baking tokens back to weights? | 1 | [removed] | 2025-01-03T21:25:00 | https://www.reddit.com/r/LocalLLaMA/comments/1hsxhih/is_there_any_papertopologyresearch_about_llm/ | Economy_Apple_4617 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hsxhih | false | null | t3_1hsxhih | /r/LocalLLaMA/comments/1hsxhih/is_there_any_papertopologyresearch_about_llm/ | false | false | self | 1 | null |
PubMedBERT Embeddings Model2Vec: 100K - 8M parameter static vector models | 26 | 2025-01-03T21:30:16 | https://huggingface.co/collections/NeuML/pubmedbert-embeddings-m2v-67785089778b3f19be6c39c5 | davidmezzetti | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1hsxlxd | false | null | t3_1hsxlxd | /r/LocalLLaMA/comments/1hsxlxd/pubmedbert_embeddings_model2vec_100k_8m_parameter/ | false | false | 26 | {'enabled': False, 'images': [{'id': 'CAjKsBgxOKas7kElPGxlX6K0usnWM-NBncv9nQT4FGs', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/U9D1uBZimHLJC3IVykHVbS1g98qAdcKtsU09FJwoiCQ.jpg?width=108&crop=smart&auto=webp&s=c9829e91b3d16295513a5f93f04d7c7383b3a326', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/U9D1uBZimHLJC3IVykHVbS1g98qAdcKtsU09FJwoiCQ.jpg?width=216&crop=smart&auto=webp&s=26575e828107553e04002bac5ca6683f8309f98d', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/U9D1uBZimHLJC3IVykHVbS1g98qAdcKtsU09FJwoiCQ.jpg?width=320&crop=smart&auto=webp&s=c43c90de4b059207e35a176623b7013410a268a5', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/U9D1uBZimHLJC3IVykHVbS1g98qAdcKtsU09FJwoiCQ.jpg?width=640&crop=smart&auto=webp&s=fced265666b3ebf83d008922ed6e2f4fb1914f74', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/U9D1uBZimHLJC3IVykHVbS1g98qAdcKtsU09FJwoiCQ.jpg?width=960&crop=smart&auto=webp&s=c16c1c7c296cbc7c0aba22103b59a2945d2272c3', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/U9D1uBZimHLJC3IVykHVbS1g98qAdcKtsU09FJwoiCQ.jpg?width=1080&crop=smart&auto=webp&s=d88f74666e534e6098109352eaaeb275b45d918e', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/U9D1uBZimHLJC3IVykHVbS1g98qAdcKtsU09FJwoiCQ.jpg?auto=webp&s=16ed70e287a0d71b19a6105dc4c8b345a72ea774', 'width': 1200}, 'variants': {}}]} |
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Best LLM for character creation? | 3 | So I'm a some-time character creator within the [Backyard.AI](http://Backyard.AI) hub and I've been using their cloud models (magnum 1 72b, command r 104b) using special character creation cards I made ages ago, but I feel like with all the constant developments in the open source AI field I might be missing out on some of the best models for this purpose. Locally I've got 40gb VRAM but I'm happy to run character creation cards slowly as long as the content quality is good. I hear y'all singing the praises of Mistral Large and Midnight Miqu etc, but about all sorts of things never related to the niche of character creation that I like to indulge in.
I figure creative writing and character development probably have some overlap but I don't really engage in creative writing exercises with AI other than for character creation so I can't really be sure.
So that being said, what models would y'all recommend for this particular usage purpose? I'm keen to hear from the broader (not just Backyard.AI) LLM community about this and for those of us in the know there's no where better than r/LocalLLama \- so here I am, all ears! | 2025-01-03T21:55:25 | https://www.reddit.com/r/LocalLLaMA/comments/1hsy7g9/best_llm_for_character_creation/ | Gerdel | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hsy7g9 | false | null | t3_1hsy7g9 | /r/LocalLLaMA/comments/1hsy7g9/best_llm_for_character_creation/ | false | false | self | 3 | {'enabled': False, 'images': [{'id': 'cJ68YRfcyKxO_TrM223_zvAFQZqprWyI9Rh8k-WDL6Y', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/SfWhTb81zzWhx5Xj9aqzlpO0ZfgQJcTKS6baoQWuSSI.jpg?width=108&crop=smart&auto=webp&s=9efd57d2e9fbd247c71a12e86e7fa142f9132f08', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/SfWhTb81zzWhx5Xj9aqzlpO0ZfgQJcTKS6baoQWuSSI.jpg?width=216&crop=smart&auto=webp&s=7a2707fc7b707f2b5d9cbf7023fde65b8087eaef', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/SfWhTb81zzWhx5Xj9aqzlpO0ZfgQJcTKS6baoQWuSSI.jpg?width=320&crop=smart&auto=webp&s=d788e43dc38e6478e448faec80ae66f389e47b80', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/SfWhTb81zzWhx5Xj9aqzlpO0ZfgQJcTKS6baoQWuSSI.jpg?width=640&crop=smart&auto=webp&s=dbb65d41fe23d8d53ff517be34aa1c2886e38509', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/SfWhTb81zzWhx5Xj9aqzlpO0ZfgQJcTKS6baoQWuSSI.jpg?width=960&crop=smart&auto=webp&s=bf7cd861f135f566167b8c1fb5e8bc8f0c0d572a', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/SfWhTb81zzWhx5Xj9aqzlpO0ZfgQJcTKS6baoQWuSSI.jpg?width=1080&crop=smart&auto=webp&s=32f84d3497ee07d1fbbd5954df09e09a2cd89d00', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/SfWhTb81zzWhx5Xj9aqzlpO0ZfgQJcTKS6baoQWuSSI.jpg?auto=webp&s=44b69d92c04fca9ef125bb2a479a8cf6ead0401c', 'width': 1200}, 'variants': {}}]} |
Help choosing a gpu | 4 | I have an old server turned desktop that’s running an old server grade Xeon and 64GB DDR3 ECC RAM. The motherboard supports up to three GPUs. I’m wondering if it’s worth getting a GPU or two and what your recommendations would be. Or if my system is too old.
I’m running it on nixos and am open to Nvidia and AMD gpus. | 2025-01-03T22:18:48 | https://www.reddit.com/r/LocalLLaMA/comments/1hsyrdy/help_choosing_a_gpu/ | masterfink | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hsyrdy | false | null | t3_1hsyrdy | /r/LocalLLaMA/comments/1hsyrdy/help_choosing_a_gpu/ | false | false | self | 4 | null |
Got Segment-Anything 2 running totally in the browser, using WebGPU! Source code linked | 57 | 2025-01-03T22:31:49 | https://github.com/lucasgelfond/webgpu-sam2 | lucasgelfond | github.com | 1970-01-01T00:00:00 | 0 | {} | 1hsz234 | false | null | t3_1hsz234 | /r/LocalLLaMA/comments/1hsz234/got_segmentanything_2_running_totally_in_the/ | false | false | 57 | {'enabled': False, 'images': [{'id': 'jULZzBmrHbTtxtr5z93suW-CYSr6ptnqHLKbDEiJKK4', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/Ims1KPvZIXMetGHtLfy-ujfxB9QPYDUJlWg9lPvUkDs.jpg?width=108&crop=smart&auto=webp&s=95441d1d0351e2b52054f437d2eb4516e3b1d3a2', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/Ims1KPvZIXMetGHtLfy-ujfxB9QPYDUJlWg9lPvUkDs.jpg?width=216&crop=smart&auto=webp&s=751433760914160b2a2c49101d7f6367ea0d8bf7', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/Ims1KPvZIXMetGHtLfy-ujfxB9QPYDUJlWg9lPvUkDs.jpg?width=320&crop=smart&auto=webp&s=476996c1c7806f96894f6f790df4bcb12e1b979a', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/Ims1KPvZIXMetGHtLfy-ujfxB9QPYDUJlWg9lPvUkDs.jpg?width=640&crop=smart&auto=webp&s=529cdb47472367119e4d0aba6603cf3853759907', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/Ims1KPvZIXMetGHtLfy-ujfxB9QPYDUJlWg9lPvUkDs.jpg?width=960&crop=smart&auto=webp&s=d223446d1b0264e52c197384b27810bfc89270a1', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/Ims1KPvZIXMetGHtLfy-ujfxB9QPYDUJlWg9lPvUkDs.jpg?width=1080&crop=smart&auto=webp&s=41e763f06e674168b0fc4a7e22f3a8033b9b1e77', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/Ims1KPvZIXMetGHtLfy-ujfxB9QPYDUJlWg9lPvUkDs.jpg?auto=webp&s=d2542b1d217491759e45d9daad76b35daba033bd', 'width': 1200}, 'variants': {}}]} |
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I'm getting started with LLMs on Raspberry Pi 5: Using Ollama, Hailo AI Hat and Agents | 3 | I'm new to this area, so I hope my question isn't silly: I need to run my project with a Large Language Model (LLM) using Ollama, Visual Studio Code (VS Code), the Hailo AI Hat, Python and the Raspberry Pi 5.
Will using the AI Hat improve performance?
My application involves agents. What are the best models to use in this context? | 2025-01-03T22:40:25 | https://www.reddit.com/r/LocalLLaMA/comments/1hsz92o/im_getting_started_with_llms_on_raspberry_pi_5/ | OutrageousAspect7459 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hsz92o | false | null | t3_1hsz92o | /r/LocalLLaMA/comments/1hsz92o/im_getting_started_with_llms_on_raspberry_pi_5/ | false | false | self | 3 | null |
I asked a stupid question and got a "stupid" answer... Can someone translate from AI? | 1 | 2025-01-03T23:08:49 | Bugajpcmr | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1hszwft | false | null | t3_1hszwft | /r/LocalLLaMA/comments/1hszwft/i_asked_a_stupid_question_and_got_a_stupid_answer/ | false | false | 1 | {'enabled': True, 'images': [{'id': 'goNmamGk8ISHjgUQOkel8Kq4m6hg5xR565CIJtDVgQ0', 'resolutions': [{'height': 84, 'url': 'https://preview.redd.it/8sw7blor1vae1.png?width=108&crop=smart&auto=webp&s=dcc1010bfa0b26b191a93f9c6d08c91e0c3e81c8', 'width': 108}, {'height': 168, 'url': 'https://preview.redd.it/8sw7blor1vae1.png?width=216&crop=smart&auto=webp&s=4e15d2ae12f4a11ec7906eb3acc64b57e36fa274', 'width': 216}, {'height': 249, 'url': 'https://preview.redd.it/8sw7blor1vae1.png?width=320&crop=smart&auto=webp&s=375eb9c8120419a58b96a14edd40b4630c705996', 'width': 320}, {'height': 499, 'url': 'https://preview.redd.it/8sw7blor1vae1.png?width=640&crop=smart&auto=webp&s=e6546a566c084eb43839848b61bad640becd050b', 'width': 640}, {'height': 749, 'url': 'https://preview.redd.it/8sw7blor1vae1.png?width=960&crop=smart&auto=webp&s=523ab70e426809209eee906f824048d08f0807fa', 'width': 960}, {'height': 843, 'url': 'https://preview.redd.it/8sw7blor1vae1.png?width=1080&crop=smart&auto=webp&s=3cca45ca271e2031177a7e9f40931e9526c94f8b', 'width': 1080}], 'source': {'height': 1428, 'url': 'https://preview.redd.it/8sw7blor1vae1.png?auto=webp&s=19e07af641f57c400d386905d8e43e2f6a8b030f', 'width': 1828}, 'variants': {}}]} |
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I asked a question about IP and got a "weird" answer. | 1 | 2025-01-03T23:12:32 | Bugajpcmr | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1hszzhq | false | null | t3_1hszzhq | /r/LocalLLaMA/comments/1hszzhq/i_asked_a_question_about_ip_and_got_a_weird_answer/ | false | false | 1 | {'enabled': True, 'images': [{'id': 'VBN_QVxQDlYho5LP7ymMRXf6QzdeMGdLg7Go3TW2aYs', 'resolutions': [{'height': 84, 'url': 'https://preview.redd.it/7hy4kffj2vae1.png?width=108&crop=smart&auto=webp&s=56639f703c53dae8c674f7485e43b39081a123a6', 'width': 108}, {'height': 168, 'url': 'https://preview.redd.it/7hy4kffj2vae1.png?width=216&crop=smart&auto=webp&s=4c4cb7b0a9bc86b07944cc9fa739ca4517ebad13', 'width': 216}, {'height': 249, 'url': 'https://preview.redd.it/7hy4kffj2vae1.png?width=320&crop=smart&auto=webp&s=cc7c0546932549e9e3a6bdc0b59be2e1d528f473', 'width': 320}, {'height': 499, 'url': 'https://preview.redd.it/7hy4kffj2vae1.png?width=640&crop=smart&auto=webp&s=b73ffd11ec055b48a77078e2fe15197887e8e129', 'width': 640}, {'height': 749, 'url': 'https://preview.redd.it/7hy4kffj2vae1.png?width=960&crop=smart&auto=webp&s=d177e97c195f02f71f1c7b0ec1733867cb9f0fe2', 'width': 960}, {'height': 843, 'url': 'https://preview.redd.it/7hy4kffj2vae1.png?width=1080&crop=smart&auto=webp&s=f5944f02d17d62f89d602025228ba10d2e03f0a5', 'width': 1080}], 'source': {'height': 1428, 'url': 'https://preview.redd.it/7hy4kffj2vae1.png?auto=webp&s=ce5c2d9de0b8e2bb5df79c27c3cc7f2ada5e57b3', 'width': 1828}, 'variants': {}}]} |
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Need Help Optimizing RAG System with PgVector, Qwen Model, and BGE-Base Reranker | 1 | [removed] | 2025-01-03T23:43:53 | https://www.reddit.com/r/LocalLLaMA/comments/1ht0oqe/need_help_optimizing_rag_system_with_pgvector/ | FlakyConference9204 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht0oqe | false | null | t3_1ht0oqe | /r/LocalLLaMA/comments/1ht0oqe/need_help_optimizing_rag_system_with_pgvector/ | false | false | self | 1 | null |
What do you expect from an AGI? | 0 | We have heard many definitions of AGI from different companies and influential people.
**But what would you personally realistically expect from an AI to say that it is "generally smart enough" for you?**
A practical example (and a long story, sorry).
A few days ago my laser printer broke. The intermediate transfer belt got damaged presumably because of air humidity changes in my apartment. A humid autumn caused clots of toner and paper dust, and then hot heating made the clots hard and they left permanent marks on the ITB.
I spent almost 10 hours to research the topic, first to find out what might be the reasons for the print issue I'm experiencing, and the AI was not that useful, mentioning only the toner issues and not anything about the ITB. Only after I found myself that there was this thing called ITB and mentioned it to the AI, it "admitted" that ITB could indeed be the issue. Then I had to research the repair options and costs, to find out that repairing is almost unfeasible because the ITB unit costs as a new printer. However, then I discovered that it's possible to order the belt alone from China. Replacing the belt alone would be quite tricky and it's not officially supported, and there are only a few videos about it.
Then I also wanted to find out how other printer companies deal with this. I found that Brother printers have a user-replaceable ITB unit, and in general, have more user-serviceable parts! However, some users said that Brother color printing quality is not as good as HP's. I'm still collecting the evidence if this is true also for their newest models, which use LEDs instead of lasers.
Then I researched my options (repair/buy a new printer - but which one, to avoid this issue in the future or have easier repairs and not lose the print quality I had with my current printer). I found that LLMs can help only if I provide strong leads and keywords, but they rarely come up with the most important keywords and important decision-making facts.
Being a somewhat perfectionist and overthinker, I quite often get in situations when I want to research reviews and in-depth technical information that comes up in obscure internet forums or video reviews (and quite often they are in Russian because Russians are known for trying to repair everything just to save on costs, even if it requires spending many hours).
**So, to resume, for me personally an AGI would be an AI that could do all of this research for me. It should be able to start with a vague description of the problem, learning more options as it goes on and collecting the most relevant facts to finally come up with the list of options for me to decide on.**
For example, in this case, I would start with the question "My printer has this issue - what should I do?" and the AI should collect information online, guide me through troubleshooting, and discover the existence and weaknesses of ITB on its own. Then I would ask it to evaluate repair options - again, it should find both options of replacing the entire unit or replacing the belt alone, and lead me to stores with pricing. Then I would ask "If I decide to buy a new printer that makes it easier to deal with this ITB issue in the future, what should I buy and what would the compromises be when compared to my current printer?" and the AI should again do the research and come up with up-to-date models that have user-replaceable ITB and also gather real print quality comparisons.
Seems a simple problem, right? It does not require a PhD. However, it requires dynamic use of internet search, critical thinking, and the ability to delve deeper. It also would be great if the "AGI" had a local database stored on my system where it had collected my previous request patterns and would know my personality well enough to know what usually is important to me - longevity, user-serviceability and quality, and not printing speed or "smart" features.
Will we reach this level from local models this year? I am doubtful. Using current LLMs for such kinds of research feels like having three wishes from a devil - you ask your LLM something, it replies with something superficial, then you discover something on your own and ask the LLM why it didn't mention this, and it "admits" it did not think it's important (of course - because it does not delve deep enough), and so on. | 2025-01-04T00:49:48 | https://www.reddit.com/r/LocalLLaMA/comments/1ht24lh/what_do_you_expect_from_an_agi/ | martinerous | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht24lh | false | null | t3_1ht24lh | /r/LocalLLaMA/comments/1ht24lh/what_do_you_expect_from_an_agi/ | false | false | self | 0 | null |
CAG is the Future. It's about to get real people. | 147 | Saw a thing about "CAG" and was like okay let's see what the flavor of the day is... This is different. This is going to change things.
[https://arxiv.org/abs/2412.15605](https://arxiv.org/abs/2412.15605)
There is a github I am not affiliated with but has a solution up already. its hhhuang/CAG
There is also already research about using for 4-bit optimizations, model and system level optimizations also. You'll have to search for those I lost them in the flurry. I'm excited. Maybe I can get something performant working on my phone.
Peace :) | 2025-01-04T01:09:35 | https://www.reddit.com/r/LocalLLaMA/comments/1ht2jvn/cag_is_the_future_its_about_to_get_real_people/ | mr_happy_nice | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht2jvn | false | null | t3_1ht2jvn | /r/LocalLLaMA/comments/1ht2jvn/cag_is_the_future_its_about_to_get_real_people/ | false | false | self | 147 | null |
LLM Farm (iOS) - gguf downloaded respond with garbage. How to run random LLM from HuggingFace? | 2 | I’m playing with lots of native iOS apps for running LLMs locally. LLM farm is near top since it supports vision models.
But…. I don’t have good luck getting downloaded gguf files to work properly.
For example, qwen2.5-coder-3b-instruct-fp16 shows complete garbage in response to my queries.
How to now how to parameterize LLMs? For example, I assume would work better if I knew the prompt template to choose, or questions such as if the LLM expects BOS/EOS/special-tokens… etc.
What else can cause such garbage response.
Shouldn’t the GGUF file encode all the info in, and I shouldn’t have to configure?
Perhaps there are better apps that know how to read metadata from gguf to know how to run it? Or at least the app would say “not supported because blah blah”.
Also, I have iPhone 16 pro max with 8gB memory. So
I’m surprised when LLm farm crashes on a measly 2GB LFG if I download. Perhaps again is because some feature in the LLm it doesn’t support. | 2025-01-04T01:14:40 | https://www.reddit.com/r/LocalLLaMA/comments/1ht2npq/llm_farm_ios_gguf_downloaded_respond_with_garbage/ | Puzzleheaded-Fly4322 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht2npq | false | null | t3_1ht2npq | /r/LocalLLaMA/comments/1ht2npq/llm_farm_ios_gguf_downloaded_respond_with_garbage/ | false | false | self | 2 | null |
How LLMs sort lists? | 0 | I was refactoring a few large files with a bunch of imports and it struck me I really don't know how it can do sorting. Does it approximate or sort precisely using external scripts? I used Gemini 1206 in Gemini Coder extension (refactoring command). | 2025-01-04T01:34:05 | https://www.reddit.com/r/LocalLLaMA/comments/1ht31z7/how_llms_sort_lists/ | robertpiosik | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht31z7 | false | null | t3_1ht31z7 | /r/LocalLLaMA/comments/1ht31z7/how_llms_sort_lists/ | false | false | self | 0 | null |
NSFW / Uncensored Text Generation Model | 1 | [removed] | 2025-01-04T01:49:20 | https://www.reddit.com/r/LocalLLaMA/comments/1ht3cur/nsfw_uncensored_text_generation_model/ | gorgonation | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht3cur | false | null | t3_1ht3cur | /r/LocalLLaMA/comments/1ht3cur/nsfw_uncensored_text_generation_model/ | false | false | nsfw | 1 | null |
Looking for NSFW / Uncensored Text Generation Model | 1 | [removed] | 2025-01-04T01:52:34 | https://www.reddit.com/r/LocalLLaMA/comments/1ht3f3j/looking_for_nsfw_uncensored_text_generation_model/ | PropertyLoover | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht3f3j | false | null | t3_1ht3f3j | /r/LocalLLaMA/comments/1ht3f3j/looking_for_nsfw_uncensored_text_generation_model/ | false | false | nsfw | 1 | null |
Need Help Optimizing RAG System with PgVector, Qwen Model, and BGE-Base Reranker | 1 | [removed] | 2025-01-04T01:56:44 | https://www.reddit.com/r/LocalLLaMA/comments/1ht3i7s/need_help_optimizing_rag_system_with_pgvector/ | FlakyConference9204 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht3i7s | false | null | t3_1ht3i7s | /r/LocalLLaMA/comments/1ht3i7s/need_help_optimizing_rag_system_with_pgvector/ | false | false | self | 1 | null |
Grok 2 being open-sourced soon? | 126 | https://x.com/elonmusk/status/1875357350393246114 | 2025-01-04T02:19:20 | https://www.reddit.com/r/LocalLLaMA/comments/1ht3ynl/grok_2_being_opensourced_soon/ | Educational_Grab_473 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht3ynl | false | null | t3_1ht3ynl | /r/LocalLLaMA/comments/1ht3ynl/grok_2_being_opensourced_soon/ | false | false | self | 126 | {'enabled': False, 'images': [{'id': 'KbG9WkQU6tbc3TVmCuIG9Vq0Nt0ki_GgQ8T5pYxBSFA', 'resolutions': [{'height': 108, 'url': 'https://external-preview.redd.it/vTyAuWpdPX8CZ1l7w9kd8GMjFQrEjVtGadgWWQDyEWQ.jpg?width=108&crop=smart&auto=webp&s=1407611fdcb97aad23445d5495b1331c5f744889', 'width': 108}], 'source': {'height': 200, 'url': 'https://external-preview.redd.it/vTyAuWpdPX8CZ1l7w9kd8GMjFQrEjVtGadgWWQDyEWQ.jpg?auto=webp&s=6f62ef7c2cb42c30faf5a29acd4e0f70254e1a96', 'width': 200}, 'variants': {}}]} |
7B reasoning model! | 1 | [removed] | 2025-01-04T02:35:26 | http://hf.co/brahmairesearch/x1-7B-v0.1 | kstyagi_ | hf.co | 1970-01-01T00:00:00 | 0 | {} | 1ht49qk | false | null | t3_1ht49qk | /r/LocalLLaMA/comments/1ht49qk/7b_reasoning_model/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'tmV9-Hk1exolZVgBJk43kmS2ENnRHvEQlfpn5VLjJds', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/MJlAOVWOPfPYMTOHHJYXkRmBjUghmZum81Jd3-YcOQ8.jpg?width=108&crop=smart&auto=webp&s=a561c87129083a7a33be258616c87cc4ca94fdfa', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/MJlAOVWOPfPYMTOHHJYXkRmBjUghmZum81Jd3-YcOQ8.jpg?width=216&crop=smart&auto=webp&s=86ab7d99b9dc464a2571af5659b53a3665607721', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/MJlAOVWOPfPYMTOHHJYXkRmBjUghmZum81Jd3-YcOQ8.jpg?width=320&crop=smart&auto=webp&s=dfffe4ce86877971fd4870e9c6c8971f571ff3b5', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/MJlAOVWOPfPYMTOHHJYXkRmBjUghmZum81Jd3-YcOQ8.jpg?width=640&crop=smart&auto=webp&s=212beaee5ca8d15b52c27817cd67ba3f502b206f', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/MJlAOVWOPfPYMTOHHJYXkRmBjUghmZum81Jd3-YcOQ8.jpg?width=960&crop=smart&auto=webp&s=46e8ad33e38afbb12173ebc9acb5f5bf823513a5', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/MJlAOVWOPfPYMTOHHJYXkRmBjUghmZum81Jd3-YcOQ8.jpg?width=1080&crop=smart&auto=webp&s=d756b23a349bc508902b972bf13ecdd529d64fb6', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/MJlAOVWOPfPYMTOHHJYXkRmBjUghmZum81Jd3-YcOQ8.jpg?auto=webp&s=5921f2201f52b97820a9009223d15883f5e02722', 'width': 1200}, 'variants': {}}]} |
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Can I use images and scripts generated with Meta AI (Llama 3.2) for commercial purpose? | 1 | [removed] | 2025-01-04T02:43:20 | https://www.reddit.com/r/LocalLLaMA/comments/1ht4f05/can_i_use_images_and_scripts_generated_with_meta/ | PlatypusFast3561 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht4f05 | false | null | t3_1ht4f05 | /r/LocalLLaMA/comments/1ht4f05/can_i_use_images_and_scripts_generated_with_meta/ | false | false | self | 1 | null |
Help with ollama and the Continue VSCode extension? Sometimes it works, sometimes it fails spectacularly | 1 | [removed] | 2025-01-04T03:20:59 | https://www.reddit.com/r/LocalLLaMA/comments/1ht54ih/help_with_ollama_and_the_continue_vscode/ | im_dylan_it | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht54ih | false | null | t3_1ht54ih | /r/LocalLLaMA/comments/1ht54ih/help_with_ollama_and_the_continue_vscode/ | false | false | self | 1 | null |
Llama 2 ported to... Sega Dreamcast ! | 1 | [removed] | 2025-01-04T03:26:51 | celsowm | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1ht58h2 | false | null | t3_1ht58h2 | /r/LocalLLaMA/comments/1ht58h2/llama_2_ported_to_sega_dreamcast/ | false | false | 1 | {'enabled': True, 'images': [{'id': '5z5aAgcy9c3jNeYHzGeUHKtiOnFD7OrB1emrSzyJA44', 'resolutions': [{'height': 81, 'url': 'https://preview.redd.it/ax15sl8ybwae1.png?width=108&crop=smart&auto=webp&s=235f7d59487701561d4fb6bd118438685285f2af', 'width': 108}, {'height': 162, 'url': 'https://preview.redd.it/ax15sl8ybwae1.png?width=216&crop=smart&auto=webp&s=f4ba7a92b391f55f527067633b4dae5aff65a9a3', 'width': 216}, {'height': 240, 'url': 'https://preview.redd.it/ax15sl8ybwae1.png?width=320&crop=smart&auto=webp&s=e92256b80eba92f0da226e5d4e4672a90b23cbe7', 'width': 320}, {'height': 480, 'url': 'https://preview.redd.it/ax15sl8ybwae1.png?width=640&crop=smart&auto=webp&s=d99cb67878458ce76355f445aefbf104c0d2d84f', 'width': 640}, {'height': 720, 'url': 'https://preview.redd.it/ax15sl8ybwae1.png?width=960&crop=smart&auto=webp&s=40b81068ddc5fb2764db725747d810e7aa373a07', 'width': 960}, {'height': 810, 'url': 'https://preview.redd.it/ax15sl8ybwae1.png?width=1080&crop=smart&auto=webp&s=9cd3dd5cf200fa38a55ec0776acfe584c6b07f87', 'width': 1080}], 'source': {'height': 960, 'url': 'https://preview.redd.it/ax15sl8ybwae1.png?auto=webp&s=efe0e3db70f79b1987ea09b82597017ea1ba51fe', 'width': 1280}, 'variants': {}}]} |
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How to make llama-cpp-python use GPU? | 6 | Hey, I'm a little bit new to all of this local Ai thing, and now I'm able to run small models (7B-11B) through command using my GPU (rx 5500XT 8GB with ROCm), but now I'm trying to set up a python script to process some text and of course, do it on the GPU, but it automatically loads it into the CPU, I have checked and tried unninstalling the default package and loading the hip Las environment variable, but still loads it on the Cpu.
Any advice? | 2025-01-04T03:31:34 | https://www.reddit.com/r/LocalLLaMA/comments/1ht5bmc/how_to_make_llamacpppython_use_gpu/ | JuCaDemon | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht5bmc | false | null | t3_1ht5bmc | /r/LocalLLaMA/comments/1ht5bmc/how_to_make_llamacpppython_use_gpu/ | false | false | self | 6 | null |
Anyone else feel like chatgpt has become worse? ( example hallucination, and constant agreement with user without questioning) | 13 | Here is a conversation - https://chatgpt.com/share/6778b248-07c8-8005-9511-a8b8463c5626
Btw, Veternary recommended calorie requirements for a cat is usually around 200 calories a day.
I tried the same with claude and immediately it corrected me. Something is off with openAI bros, this is worse than gpt 3.5 wtf. | 2025-01-04T04:02:51 | https://www.reddit.com/r/LocalLLaMA/comments/1ht5wi2/anyone_else_feel_like_chatgpt_has_become_worse/ | EggplantKlutzy1837 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht5wi2 | false | null | t3_1ht5wi2 | /r/LocalLLaMA/comments/1ht5wi2/anyone_else_feel_like_chatgpt_has_become_worse/ | false | false | self | 13 | {'enabled': False, 'images': [{'id': 'Nyuu7POyhy6govfJ1dcuznEdiKSvWYvY75CrbkKZk54', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/FFgFDVf9yDNjhoip2yXpNCPko82IyWUZ4rR9l5sQd1Q.jpg?width=108&crop=smart&auto=webp&s=1c9fdd18b399712019363db42aafb980b94bd314', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/FFgFDVf9yDNjhoip2yXpNCPko82IyWUZ4rR9l5sQd1Q.jpg?width=216&crop=smart&auto=webp&s=899c4a23b4ceac10e86c1f39517d489870146375', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/FFgFDVf9yDNjhoip2yXpNCPko82IyWUZ4rR9l5sQd1Q.jpg?width=320&crop=smart&auto=webp&s=f0fbf30be58ec54707a24cb4ac47d68af24442f7', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/FFgFDVf9yDNjhoip2yXpNCPko82IyWUZ4rR9l5sQd1Q.jpg?width=640&crop=smart&auto=webp&s=e590319308efb90d50448579fb76b003782dec8c', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/FFgFDVf9yDNjhoip2yXpNCPko82IyWUZ4rR9l5sQd1Q.jpg?width=960&crop=smart&auto=webp&s=e25bf929190c7aca5bc237df824850c31f043113', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/FFgFDVf9yDNjhoip2yXpNCPko82IyWUZ4rR9l5sQd1Q.jpg?width=1080&crop=smart&auto=webp&s=bb8c7e2b754942d06a77b1979c63552b76523e40', 'width': 1080}], 'source': {'height': 900, 'url': 'https://external-preview.redd.it/FFgFDVf9yDNjhoip2yXpNCPko82IyWUZ4rR9l5sQd1Q.jpg?auto=webp&s=e3bf69e1a2674fdfdf6fdb17b1bc4de5488bd3eb', 'width': 1600}, 'variants': {}}]} |
How good is DeepSeek AI? | 1 | [removed] | 2025-01-04T04:16:01 | https://www.reddit.com/r/LocalLLaMA/comments/1ht6553/how_good_is_deepseek_ai/ | No1tan1ts3d | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht6553 | false | null | t3_1ht6553 | /r/LocalLLaMA/comments/1ht6553/how_good_is_deepseek_ai/ | false | false | self | 1 | null |
Starting discord for AI agent building/keeping up with gen AI | 1 | [removed] | 2025-01-04T04:21:08 | [deleted] | 1970-01-01T00:00:00 | 0 | {} | 1ht68gh | false | null | t3_1ht68gh | /r/LocalLLaMA/comments/1ht68gh/starting_discord_for_ai_agent_buildingkeeping_up/ | false | false | default | 1 | null |
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ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use | 66 | 🚀 Introducing **ScreenSpot-Pro** – the first benchmark driving Multi-modal LLMs into high-resolution professional GUI-Agent and computer-use environments!
📊 While GUI agents excel at general tasks like web browsing, professional applications remain underexplored.
🔹 ScreenSpot-Pro includes 23 applications spanning 5 industries and 3 operating systems, featuring real-world tasks annotated by experts.
🔹 These environments pose unique challenges – higher resolutions, smaller targets, and intricate workflows.
📉 Current models fall short – #GPT4o achieves a mere 0.8%, while the best grounding MLLM reaches only 18.9%.
🆒 Reducing image size improves results (up to 40.2%), but there’s still a long way to go.
💡 ScreenSpot-Pro reveals key gaps and paves the way for advancing GUI agents in professional settings. It’s time to push beyond web and mobile into next-gen AI productivity tools!
🏝️ Twitter: [https://x.com/ChiYeung\_Law/status/1875179243401019825](https://x.com/ChiYeung_Law/status/1875179243401019825)
🤗 Blog: [https://huggingface.co/blog/Ziyang/screenspot-pro](https://huggingface.co/blog/Ziyang/screenspot-pro)
📈 Project & Leaderboard: [https://gui-agent.github.io/grounding-leaderboard/](https://gui-agent.github.io/grounding-leaderboard/)
📄 Paper Link: [https://likaixin2000.github.io/papers/ScreenSpot\_Pro.pdf](https://likaixin2000.github.io/papers/ScreenSpot_Pro.pdf)
📘 Data: [https://huggingface.co/datasets/likaixin/ScreenSpot-Pro](https://huggingface.co/datasets/likaixin/ScreenSpot-Pro)
https://preview.redd.it/qh130pn1rwae1.jpg?width=1804&format=pjpg&auto=webp&s=2c0e1c5965d3e9300fa26cf5268bfda0c1fa94b0
| 2025-01-04T04:52:15 | https://www.reddit.com/r/LocalLLaMA/comments/1ht6s3m/screenspotpro_gui_grounding_for_professional/ | cylaw01 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht6s3m | false | null | t3_1ht6s3m | /r/LocalLLaMA/comments/1ht6s3m/screenspotpro_gui_grounding_for_professional/ | false | false | 66 | {'enabled': False, 'images': [{'id': 'qL7rAZJ9RGHjDRtyXHrl8lTPQDxMysSMOHPMNY4m34o', 'resolutions': [{'height': 99, 'url': 'https://external-preview.redd.it/nSmSzAqPE43umnzILE37k0nhmn43FpFFTHeU2oP04ro.jpg?width=108&crop=smart&auto=webp&s=2515d2eeb933a56fdbe2d5887c67f6873c8282a0', 'width': 108}, {'height': 198, 'url': 'https://external-preview.redd.it/nSmSzAqPE43umnzILE37k0nhmn43FpFFTHeU2oP04ro.jpg?width=216&crop=smart&auto=webp&s=3fedfe617f184f531a13e183e880fcc5b2ef1057', 'width': 216}, {'height': 293, 'url': 'https://external-preview.redd.it/nSmSzAqPE43umnzILE37k0nhmn43FpFFTHeU2oP04ro.jpg?width=320&crop=smart&auto=webp&s=16e3b1ef544acbcf631c1893d04835cdfc9c1862', 'width': 320}, {'height': 586, 'url': 'https://external-preview.redd.it/nSmSzAqPE43umnzILE37k0nhmn43FpFFTHeU2oP04ro.jpg?width=640&crop=smart&auto=webp&s=6b4b5ab5639f3a9e1fba43bed3bcdc4342a09846', 'width': 640}, {'height': 880, 'url': 'https://external-preview.redd.it/nSmSzAqPE43umnzILE37k0nhmn43FpFFTHeU2oP04ro.jpg?width=960&crop=smart&auto=webp&s=345edeb1c854a3ecee92d43290123150ffa5d04b', 'width': 960}, {'height': 990, 'url': 'https://external-preview.redd.it/nSmSzAqPE43umnzILE37k0nhmn43FpFFTHeU2oP04ro.jpg?width=1080&crop=smart&auto=webp&s=addf8ded8af2e176f7bb4cb8ffa9a6365886764a', 'width': 1080}], 'source': {'height': 1100, 'url': 'https://external-preview.redd.it/nSmSzAqPE43umnzILE37k0nhmn43FpFFTHeU2oP04ro.jpg?auto=webp&s=d1a0b684d42170e7b5b060008a07ee3e750b7a02', 'width': 1200}, 'variants': {}}]} |
|
Is deepseek a fraud? | 0 | DeepSeek claims to be ChatGPT... maybe a fraud??
https://preview.redd.it/vm9e552l2xae1.png?width=1908&format=png&auto=webp&s=663c3089157637f98a6b64b75e844490fa597a10
| 2025-01-04T05:57:05 | https://www.reddit.com/r/LocalLLaMA/comments/1ht7vj8/is_deepseek_a_fraud/ | Icy_Comfortable5522 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht7vj8 | false | null | t3_1ht7vj8 | /r/LocalLLaMA/comments/1ht7vj8/is_deepseek_a_fraud/ | false | false | 0 | null |
|
Is there a paper on how mixture of experts impacts performance? | 9 | Is there a paper on how a mixture of experts and dense model of the same parameter count (across the model, not active parameters) would perform against eachother in terms of output quality? | 2025-01-04T07:08:16 | https://www.reddit.com/r/LocalLLaMA/comments/1ht8yr1/is_there_a_paper_on_how_mixture_of_experts/ | Independent_Try_6891 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht8yr1 | false | null | t3_1ht8yr1 | /r/LocalLLaMA/comments/1ht8yr1/is_there_a_paper_on_how_mixture_of_experts/ | false | false | self | 9 | null |
A few actual examples that made me believe DeepSeek V3 really shines | 163 | 1. I stumbled upon this [post](http://xhslink.com/a/8woyRy2ASEZ2) on a famous Chinese social media (xiaohongshu), which was posted on 12/31/2024 (after DeepSeek V3 was launched). The question, after translated to English, was:
​
"Help: Since yesterday, everything I hear sounds half a step lower in pitch.
Since yesterday, for no apparent reason, everything I hear sounds half a step lower in pitch, including but not limited to the school bell, household appliances like the microwave, rice cooker, and other alert tones. I am a high school senior with a background in violin and usually listen to classical music. Now, my daily life has become extremely awkward. I’m asking the knowledgeable friends here if anyone has had similar experiences or any advice."
In the original post's replies, the doctor asked whether this person took a medicine called Carbamazepine, [which has a rare side effect](https://en.wikipedia.org/wiki/Carbamazepine#cite_ref-26) that can cause this symptom that the OP described. This side effect seems to be very rare, so when the doctor asked whether the OP took this medicine and the OP replied "yes", many people got surprised that such a mysterious symptom immediately got a correct explanation in a random social media post.
So I sent the following prompt to DeepSeek V3, ChatGPT-O1, Claude 3.5 Sonnet, and Gemini Experimental 1206 models. Only DeepSeek V3 provided a response that included Carbamazepine, while all the other models listed above gave a list of explanations, but none contained Carbamazepine.
2. I tested some math questions which these models, mostly centered on probability theory, random process, and signal processing. I feel like probably due to distillation from DeepSeek R1 model, the V3 model has exceptional math capabilities (in their official benchmarks, the math related benchmarks like MATH-500 do have exceptionally high scores). Especially, on the following 2 questions:
\`\`\`
In triangle \\( ABC \\), the sides opposite to angles \\( \\angle A, \\angle B, \\angle C \\) are \\( a, b, c \\) respectively, with \\( c = 10 \\). Given that \\( \\frac{\\cos A}{\\cos B} = \\frac{b}{a} = \\frac{4}{3} \\), and \\( P \\) is a moving point on the incircle of \\( \\triangle ABC \\), find the maximum and minimum values of the sum of the squares of the distances from point \\( P \\) to the vertices \\( A, B, C \\).
(The correct answer is Max: 88, Min: 72)
\`\`\`
And
\`\`\`
Along a one-way street there are \\( n \\) parking lots. One-by-one \\( n \\) cars numbered \\( 1, 2, 3, \\dots, n \\) enter the street. Each driver \\( i \\) heads to their favourite parking lot \\( a\_i \\) and if it is free, they occupy it. Otherwise, they continue to the next free lot and occupy it. But if all succeeding lots are occupied, they leave for good. How many sequences \\( (a\_1, a\_2, \\dots, a\_n) \\) are there such that every driver can park?
(The correct answer, as far as I am aware of, is $\\boxed{(n+1)\^{n-1}}$, but please let me know if this is wrong)
\`\`\`
DeepSeek V3 consistently outperformed GPT-4o on the 2 questions above. For the first question above, in my testings, DeepSeek V3 also had higher chance of getting it right compared to Claude Sonnet 3.5, and seems to be on par with O1 and Gemini Experimental 1206.
3. Another medically related question:
\`\`\`
A 37-year-old male patient, an employee at an electronics factory, with no past history of coronary heart disease, hypertension, or diabetes, presented to the emergency department with the chief complaint of “diarrhea for 1 day.” Because of his busy work schedule, he hoped the emergency doctor could prescribe some antidiarrheal medication.
At the triage station, the nurse measured his blood pressure at 120/80 mmHg, heart rate of 100 beats per minute, temperature of 36.3°C. He was alert, in good spirits, and had a normal facial appearance. Based on his complaints, he was referred to the internal medicine clinic.
The internist’s physical examination found that his heart rate was slightly elevated with occasional premature beats, but no other abnormalities on cardiac and pulmonary exams. Abdominal examination showed hyperactive bowel sounds without tenderness, rebound tenderness, or abdominal guarding. The physician recommended an immediate electrocardiogram (ECG) and urgent blood tests, including complete blood count, renal function, electrolytes, coagulation profile, and cardiac enzymes.
The patient entered the emergency resuscitation room for the ECG. Unexpectedly, at that moment, he suddenly experienced palpitations, chest tightness, and profuse sweating. The emergency team instructed him to lie down, the doctor assessed his condition, and the nurse initiated continuous ECG monitoring. The ECG showed ventricular tachycardia at a rate of 200 beats per minute, with an ectopic rhythm (extremely dangerous and easily leading to sudden cardiac death).
The physician first attempted pharmacological cardioversion, administering 10 mg of intravenous verapamil. However, ECG monitoring still indicated ventricular tachycardia. If this persisted, he could become hemodynamically unstable or progress to ventricular fibrillation. Just a few minutes later, the patient lost consciousness, his eyes rolled upward, and his limbs began to convulse.
After a brief consideration, the emergency department director arrived at a diagnosis of … (to be revealed). He immediately performed electrical cardioversion with a biphasic synchronized 120-Joule shock. After defibrillation, the patient’s rhythm converted, he regained consciousness, and the ventricular tachycardia finally stopped and returned to sinus rhythm at 80 beats per minute.
Half an hour later, laboratory tests showed that his CBC and coagulation profile were essentially normal. Serum sodium was 134 mmol/L, potassium 2.8 mmol/L, and chloride 95 mmol/L. He was immediately given intravenous fluids to replenish electrolytes and started on oral potassium chloride solution. Two hours later, repeat tests showed sodium 136 mmol/L and potassium 3.9 mmol/L. The patient remained under observation in the emergency department for four hours before being transferred to the intensive care unit for close monitoring.
Having read this, do you know the diagnosis? And why did he suddenly develop this acute cardiovascular emergency?
\`\`\`
I found this question on a medical-oriented social media account that posted this "puzzle question" for common readers to educate people on medical knowledge. To my surprise, ChatGPT-4o did not give the correct answer (hypokalemia) in my testing, while DeepSeek V3, Sonnet 3.5, Gemini, all gave this correct answer.
4. I recently tested several language models for their comprehension of lesser-known languages, specifically Tibetan (which is my personal interest). In my tests, DeepSeek V3 showed slightly weaker performance in Tibetan compared to Sonnet 3.5 and Gemini Experimental 1206, but it still outperformed GPT-4o and GPT-O1. I conducted these tests because I believe a general-purpose LLM should be versatile and knowledgeable in all domains of knowledge. By evaluating its performance on an “edge” domain—such as a lesser-known language—we can assess the breadth and comprehensiveness of its training.
If an LLM performs well on Tibetan without being specifically optimized for it, this suggests that its training dataset is both broad and sufficiently comprehensive. Although its proficiency in Tibetan may not be directly useful for many people, it demonstrates a depth of knowledge that could potentially benefit other minority groups requiring specialized language support.
5. Coding. I find it to have on-par ability with Sonnet 3.5. I remember asking it to debug with a Spark related question (for AWS Glue Job) and it gave very similar answer to Sonnet 3.5 & O1 which was helpful (in contrast to GPT-4o which wasn't helpful at all).
To summarize, I find DeepSeek V3 to perform very well in STEM subjects, and possess comprehensive knowledge even on edge / niche domains. As a disclaimer, I mainly tested the (1), (2), and (3) questions using Chinese while 4 and 5 using English. So your test results on the translated prompt above may vary. But still, I feel like it's a very useful model which (in theory) we can host locally and I hope it ushers an era where OSS models start to be on par with closed-source models and we will have more competition & better user experiences for all! | 2025-01-04T07:21:46 | https://www.reddit.com/r/LocalLLaMA/comments/1ht95mk/a_few_actual_examples_that_made_me_believe/ | iusazbc | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht95mk | false | null | t3_1ht95mk | /r/LocalLLaMA/comments/1ht95mk/a_few_actual_examples_that_made_me_believe/ | false | false | self | 163 | null |
Alternatives to OpenAI Voice Chat on Mobile? | 11 | This is stretching the local part of Local Llama, but does anyone have alternatives to the voice chat part of OpenAI on mobile devices? I'm fully behind open source models, but in this case I'm not really thinking about local on the mobile so much as local in the sense of private/owned where I can run my own infrastructure.
But as far as I can tell, not even Claude has voice chat in that way. | 2025-01-04T07:21:55 | https://www.reddit.com/r/LocalLLaMA/comments/1ht95pq/alternatives_to_openai_voice_chat_on_mobile/ | vert1s | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1ht95pq | false | null | t3_1ht95pq | /r/LocalLLaMA/comments/1ht95pq/alternatives_to_openai_voice_chat_on_mobile/ | false | false | self | 11 | null |
Chat and auto complete models for low end pc? | 6 | I have got i5 6200u with 16gb ram and 2gb vram which is an integrated card. I wanted to use cursor ai alternatives which can run local models. So I'm in search if there are any models that can run on my pc. Also I'm still an amateur in local models running, so I'm sorry if I seem dumb. Thanks in advance! | 2025-01-04T09:01:19 | https://www.reddit.com/r/LocalLLaMA/comments/1htaiet/chat_and_auto_complete_models_for_low_end_pc/ | kaamalvn | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htaiet | false | null | t3_1htaiet | /r/LocalLLaMA/comments/1htaiet/chat_and_auto_complete_models_for_low_end_pc/ | false | false | self | 6 | null |
smaller code models to generate manim code? | 1 | [removed] | 2025-01-04T09:20:23 | https://www.reddit.com/r/LocalLLaMA/comments/1htarjl/smaller_code_models_to_generate_manim_code/ | RoyalMaterial9614 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htarjl | false | null | t3_1htarjl | /r/LocalLLaMA/comments/1htarjl/smaller_code_models_to_generate_manim_code/ | false | false | self | 1 | null |
Learnings from building a coding agent on Llama from scratch - 5% on SWE bench lite | 1 | [removed] | 2025-01-04T09:36:21 | https://www.reddit.com/r/LocalLLaMA/comments/1htazac/learnings_from_building_a_coding_agent_on_llama/ | Flimsy_Menu1521 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htazac | false | null | t3_1htazac | /r/LocalLLaMA/comments/1htazac/learnings_from_building_a_coding_agent_on_llama/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'NBguLJqmj6JF6q9bO8LUUuxRs9EOpBw1rYzt-r6_p8g', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/NjlWxFc3JtTYooTvBGymghOrJjVdXcw8qLCbNiUGgqc.jpg?width=108&crop=smart&auto=webp&s=4cab041d5211172f585d5eaef7435b7c97fb5d8b', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/NjlWxFc3JtTYooTvBGymghOrJjVdXcw8qLCbNiUGgqc.jpg?width=216&crop=smart&auto=webp&s=6186ae43af3ca053a6a1f421c297c6c0e4c4fd99', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/NjlWxFc3JtTYooTvBGymghOrJjVdXcw8qLCbNiUGgqc.jpg?width=320&crop=smart&auto=webp&s=0c1c547b1c043fa4bab64b78ecff7b7adfafc3f6', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/NjlWxFc3JtTYooTvBGymghOrJjVdXcw8qLCbNiUGgqc.jpg?width=640&crop=smart&auto=webp&s=98af5513e3c7cd127f8f3d6e818486c6ff9ec7bd', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/NjlWxFc3JtTYooTvBGymghOrJjVdXcw8qLCbNiUGgqc.jpg?width=960&crop=smart&auto=webp&s=76489b2ea1f874434b346392d9ec9d04bca91d3f', 'width': 960}], 'source': {'height': 500, 'url': 'https://external-preview.redd.it/NjlWxFc3JtTYooTvBGymghOrJjVdXcw8qLCbNiUGgqc.jpg?auto=webp&s=49759c054794ebb2b9f32da408136efc6b49f7d3', 'width': 1000}, 'variants': {}}]} |
Best Arabic model | 1 | [removed] | 2025-01-04T10:16:20 | https://www.reddit.com/r/LocalLLaMA/comments/1htbj1k/best_arabic_model/ | depressedclassical | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htbj1k | false | null | t3_1htbj1k | /r/LocalLLaMA/comments/1htbj1k/best_arabic_model/ | false | false | self | 1 | null |
NotebookLM Telegram | 1 | 2025-01-04T10:44:27 | https://t.me/NotebookLMOfficial | jayty955 | t.me | 1970-01-01T00:00:00 | 0 | {} | 1htbws0 | false | null | t3_1htbws0 | /r/LocalLLaMA/comments/1htbws0/notebooklm_telegram/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'JKuFTfnGjsFTQSgErFEAcvQmfCQLbJd9MtR9FawPTok', 'resolutions': [{'height': 108, 'url': 'https://external-preview.redd.it/-IZhdzy9dHgx9Kz7tNCB-u1TvFizLat0yoouzpT6yjk.jpg?width=108&crop=smart&auto=webp&s=c173578f58acbbd34f2e22daa398a2b8ea9cc33f', 'width': 108}, {'height': 216, 'url': 'https://external-preview.redd.it/-IZhdzy9dHgx9Kz7tNCB-u1TvFizLat0yoouzpT6yjk.jpg?width=216&crop=smart&auto=webp&s=43aa601668c85c3ef5ade7b221f07dbd0f3b3079', 'width': 216}, {'height': 320, 'url': 'https://external-preview.redd.it/-IZhdzy9dHgx9Kz7tNCB-u1TvFizLat0yoouzpT6yjk.jpg?width=320&crop=smart&auto=webp&s=3f88e6e487373e9feda3329d1d84236026745840', 'width': 320}], 'source': {'height': 320, 'url': 'https://external-preview.redd.it/-IZhdzy9dHgx9Kz7tNCB-u1TvFizLat0yoouzpT6yjk.jpg?auto=webp&s=9777417ce8d73d3a9dfca984dd220a70f94b1aaf', 'width': 320}, 'variants': {}}]} |
||
Mini PC options capable of local LLM | 9 | I want to add a small mini PC as a dedicated LLM on my network. I was looking at the ASUS NUC 14 Pro AI ~120 TOPS. I confess I've only just started looking at this as right up until now, I was looking at building a PC but I literally just want it as a dedicated LLM machine. I've had great results with a PC running RTX 2070 Super, though GPU in AI is like storage in a Nas - I'm sure I'll want more..
I've also looked at the Jetson AGX Orin (64Gb) ~275 TOPS
I'll be grateful for any input or suggestions from anyone else doing similar on a suitable compact computer like this Nuc.not enough day | 2025-01-04T10:48:29 | https://www.reddit.com/r/LocalLLaMA/comments/1htbyqp/mini_pc_options_capable_of_local_llm/ | SithLordRising | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htbyqp | false | null | t3_1htbyqp | /r/LocalLLaMA/comments/1htbyqp/mini_pc_options_capable_of_local_llm/ | false | false | self | 9 | null |
Memory Layers at Scale | 34 | [\[2412.09764\] Memory Layers at Scale](https://arxiv.org/abs/2412.09764)
"Memory layers use a trainable key-value lookup mechanism to add extra parameters to a model without increasing FLOPs. Conceptually, sparsely activated memory layers complement compute-heavy dense feed-forward layers, providing dedicated capacity to store and retrieve information cheaply. This work takes memory layers beyond proof-of-concept, proving their utility at contemporary scale. On downstream tasks, language models augmented with our improved memory layer outperform dense models with more than twice the computation budget, as well as mixture-of-expert models when matched for both compute and parameters. We find gains are especially pronounced for factual tasks. We provide a fully parallelizable memory layer implementation, demonstrating scaling laws with up to 128B memory parameters, pretrained to 1 trillion tokens, comparing to base models with up to 8B parameters."
I think the most interesting part of this paper is that it compares the PEER model, 'Mixture of a Million Experts,' recently released by DeepMind. I originally thought this paper had been forgotten.
[\[2407.04153\] Mixture of A Million Experts](https://arxiv.org/abs/2407.04153) | 2025-01-04T10:49:55 | https://www.reddit.com/r/LocalLLaMA/comments/1htbzef/memory_layers_at_scale/ | Head_Beautiful_6603 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htbzef | false | null | t3_1htbzef | /r/LocalLLaMA/comments/1htbzef/memory_layers_at_scale/ | false | false | self | 34 | null |
Can someone test Llama3.3 on 2x3080 24gb | 1 | [removed] | 2025-01-04T11:07:57 | https://www.reddit.com/r/LocalLLaMA/comments/1htc8jx/can_someone_test_llama33_on_2x3080_24gb/ | vendor_net | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htc8jx | false | null | t3_1htc8jx | /r/LocalLLaMA/comments/1htc8jx/can_someone_test_llama33_on_2x3080_24gb/ | false | false | self | 1 | null |
What became of RAPTOR for RAG? | 22 | In the beginning of 2024 the RAPTOR paper (https://arxiv.org/html/2401.18059v1) got some attention. The idea was to combine embedding clusters and LLM summarization to construct a semantic tree structure of a document to be then used in retrieval tasks.
Back then I found the idea really compelling and made a crude implementation myself, found it promising, but somehow forgot about it and never heard much about it since.
Is anyone using it in their projects? | 2025-01-04T11:13:10 | https://www.reddit.com/r/LocalLLaMA/comments/1htcb5i/what_became_of_raptor_for_rag/ | mnze_brngo_7325 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htcb5i | false | null | t3_1htcb5i | /r/LocalLLaMA/comments/1htcb5i/what_became_of_raptor_for_rag/ | false | false | self | 22 | null |
What's the best vision model fitting on a Nvidia Jetson Orin AGX 64GB? | 1 | [removed] | 2025-01-04T11:28:33 | https://www.reddit.com/r/LocalLLaMA/comments/1htcitg/whats_the_best_vision_model_fitting_on_a_nvidia/ | bjajo | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htcitg | false | null | t3_1htcitg | /r/LocalLLaMA/comments/1htcitg/whats_the_best_vision_model_fitting_on_a_nvidia/ | false | false | self | 1 | null |
For computer vision stratup what is the next possible product that can be developed using GenAI and VLMs or LLMs | 0 | I am working in a computer vision based starup; We provide computer vision solution for manufacturing and logistics industries. Our popular products are related to inspecting the products, monitoring the safety of the workplace and measuring the productivity of an operators. All our solutions uses camera feeds as images. With this experience We are looking for possible usecases or products to develop using LLMs, VLMs and agents. | 2025-01-04T11:58:13 | https://www.reddit.com/r/LocalLLaMA/comments/1htcxl0/for_computer_vision_stratup_what_is_the_next/ | Ahmad401 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htcxl0 | false | null | t3_1htcxl0 | /r/LocalLLaMA/comments/1htcxl0/for_computer_vision_stratup_what_is_the_next/ | false | false | self | 0 | null |
Ollama 3.3:70b on Macbook Pro Max M4 - 32GB RAM. How to speed up? | 1 | [removed] | 2025-01-04T11:59:43 | https://www.reddit.com/r/LocalLLaMA/comments/1htcyb5/ollama_3370b_on_macbook_pro_max_m4_32gb_ram_how/ | sir_paperclip | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htcyb5 | false | null | t3_1htcyb5 | /r/LocalLLaMA/comments/1htcyb5/ollama_3370b_on_macbook_pro_max_m4_32gb_ram_how/ | false | false | self | 1 | null |
Good vision models to extract defined features in a JSON format | 1 | [removed] | 2025-01-04T12:03:45 | https://www.reddit.com/r/LocalLLaMA/comments/1htd0r1/good_vision_models_to_extract_defined_features_in/ | Ok-Objective-8038 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htd0r1 | false | null | t3_1htd0r1 | /r/LocalLLaMA/comments/1htd0r1/good_vision_models_to_extract_defined_features_in/ | false | false | self | 1 | null |
A hypothesis on how o3 was trained. | 1 | One takes a pre-trained model.
One then instruction fine-tunes it to follow instructions.
1. Then one throws at it multiple (proven empirically effective on the instruction-tuned model) multi-modal and multi-lingual reasoning prompts (be it tree-of-thoughts, chain-of-thoughts, reflection etc. with the condition to output additional reasoning tokens during reasoning.
2. One processes the model (with the reasoning prompt) output until it's just "Instruction, Reasoning, Output" without the underlying prompt.
3. One picks the subset with the highest reasoning scores (calculated during inference via a process and outcome reward model trained to follow subject-matter expert preferences via DPO+big dataset)
4. Then fine-tunes the standard instuction-tuned model on it.
5. Then asks the model to generate effective reasoning prompts to bootstrap reasoning prompt and reasoning dataset and scores it via a BERT model fine-tuned on the dataset of effective reasoning prompts.
6. Then fine-tune the standard model again to output effective reasoning prompts (using the BERT model as reward or loss function) and puts the things it produced into the effective reasoning prompts dataset.
Rinse and repeat (steps 1-6) until you got yourself a o1 or o3.
To encourage simplicity of outputs and too prevent overfitting use any would-be off-the-shelf regularizer(Entropy, L1,L2 etc.)
Possible problems on testing this hypothesis:
\-Getting a large dataset of empirically effective reasoning prompts
\-Building an actually effective process-reward model to score reasoning and also preventing it from overfitting or underfitting due to compute and data constraints.
\-Preventing the BERT prompt effectiveness scorer from overfitting or underfitting and make it actually capture empirical effectiveness of reasoning prompts.
\-Compute (My computer is a potato) and AWS is too expensive.
\-Data (initial datasets must be large to prevent possible biases and the reasoning model, process-reward and BERT prompt scorer from devolving into nonsense-rewarding sophists)
What are the inspirations for this method of training reasoning:
\-STaR (using reasoning to bootstrap reasoning)
\-Process reward models
\-LLAMA 3 training pipeline
\-Steiner-32b-preview (training LLMs on a data set of implicit search trees which contain reasoning) | 2025-01-04T12:11:02 | https://www.reddit.com/r/LocalLLaMA/comments/1htd4md/a_hypothesis_on_how_o3_was_trained/ | ShittyUsernane1222 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htd4md | false | null | t3_1htd4md | /r/LocalLLaMA/comments/1htd4md/a_hypothesis_on_how_o3_was_trained/ | false | false | self | 1 | null |
Potential murder mystery puzzle dataset for testing LLMs | 33 | I have create a new type of murder mystery deduction puzzle where the player needs to reason using spacial and temporal statements to find who did it. You can [test it here](https://mystery-o-matic.com) and all [the code to produce new puzzles is open-source](https://github.com/mystery-o-matic/mystery-o-matic.github.io/). A few interesting features:
* These puzzles are text only, available in English and Spanish.
* This is new type of puzzle with influences of [Cluedo](https://en.wikipedia.org/wiki/Cluedo), [Murdle](https://murdle.com/) and others, but you won't find this one in datasets (please let me know if I'm wrong!)
* Total number of clues per case is usually less than 30 and sentences are short. I suspect that the amount of context needed shouldn't be too large (however, it could be useful to include the tutorial in the prompt).
* There are some parameters to control the difficulty related with number of suspects, rooms, weapons, etc.
* If you take into account all the clues produced, you can always solve it, but usually the idea is to give the player clues that are not (so) redundant to maximize the amount of information extracted from each clue, so the difficulty level can be adjusted.
I want to know if this is good enough to produce a new dataset to test LLMs and engage with the community if there is enough interest to do it. | 2025-01-04T12:20:31 | https://www.reddit.com/r/LocalLLaMA/comments/1htd9rc/potential_murder_mystery_puzzle_dataset_for/ | galapag0 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htd9rc | false | null | t3_1htd9rc | /r/LocalLLaMA/comments/1htd9rc/potential_murder_mystery_puzzle_dataset_for/ | false | false | self | 33 | null |
Memoir+ on RunPod | 1 | u/freedomtoadventure I'm having trouble getting Memoir+ to run on Ooba. I've commented out the Docker code per your instructions, since I'm already in a Docker container and nesting would be both difficult and pointless. I can see from the logs that Qdrant is starting properly and that Memoir+ is starting up but I never see a message confirming that I have a successful start. And then the Ooba interface freezes the first time I send a prompt. I have to reload the page to get anything at all to work.
Any suggestions would be appreciated. | 2025-01-04T13:00:29 | https://www.reddit.com/r/LocalLLaMA/comments/1htdw3y/memoir_on_runpod/ | mfeldstein67 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htdw3y | false | null | t3_1htdw3y | /r/LocalLLaMA/comments/1htdw3y/memoir_on_runpod/ | false | false | self | 1 | null |
User Martin M.W tests the capabilities and limits of AI on MathOverflow | 1 | 2025-01-04T13:45:30 | https://meta.mathoverflow.net/a/6115 | v-e-k-e | meta.mathoverflow.net | 1970-01-01T00:00:00 | 0 | {} | 1hteo3j | false | null | t3_1hteo3j | /r/LocalLLaMA/comments/1hteo3j/user_martin_mw_tests_the_capabilities_and_limits/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'dimMpcZTPM3bnmkNgdbqoP9MP9mn3AKaMoy_52pHgpM', 'resolutions': [{'height': 108, 'url': 'https://external-preview.redd.it/tM_qvRvOjfMamFYAEYtm6RIvVVPM3xzlf9jnVYB-Ok0.jpg?width=108&crop=smart&auto=webp&s=08f3e89dbe684fec3ffcdee862274065ea8e6f75', 'width': 108}, {'height': 216, 'url': 'https://external-preview.redd.it/tM_qvRvOjfMamFYAEYtm6RIvVVPM3xzlf9jnVYB-Ok0.jpg?width=216&crop=smart&auto=webp&s=c74dcbdb35d71afb24a9cfcc74dcaf2e1cca64b9', 'width': 216}], 'source': {'height': 316, 'url': 'https://external-preview.redd.it/tM_qvRvOjfMamFYAEYtm6RIvVVPM3xzlf9jnVYB-Ok0.jpg?auto=webp&s=be55cf6f505e09a4f7457e27a093fd963ad97a53', 'width': 316}, 'variants': {}}]} |
||
Call for broken donor cards or coolers in the EU | 0 | Hi Locallama,
As some might have read in my past comments, I have a bunch of P40s that I am watercooling with Heatkiller 4 1080Ti FE coolers. I have long suspected that 980Ti FE and Titan X coolers will fit the P40s without much hassle. I have a spare P40 that I want to test this theory and looking for some people located in the EU with broken 980Ti FE or Titan X cards, or people who are water cooling their their cards and are willing to part with the air cooler.
While a long shot, I suspect P6000 cooler will also fit, but those are quite rare.
I am willing to offer 40€ via PayPal including shipping to Germany. Of course, I'll pay the paypal fees.
Thanks all and happy new year! | 2025-01-04T14:29:58 | https://www.reddit.com/r/LocalLLaMA/comments/1htfil5/call_for_broken_donor_cards_or_coolers_in_the_eu/ | FullstackSensei | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htfil5 | false | null | t3_1htfil5 | /r/LocalLLaMA/comments/1htfil5/call_for_broken_donor_cards_or_coolers_in_the_eu/ | false | false | self | 0 | null |
How do open source ai companies like Deepseek and Mistral make money? | 1 | [removed] | 2025-01-04T14:43:58 | https://www.reddit.com/r/LocalLLaMA/comments/1htfsj7/how_do_open_source_ai_companies_like_deepseek_and/ | 185BCE | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htfsj7 | false | null | t3_1htfsj7 | /r/LocalLLaMA/comments/1htfsj7/how_do_open_source_ai_companies_like_deepseek_and/ | false | false | self | 1 | null |
Llama3 Inference Engine - CUDA C | 77 | Hey r/LocalLLaMa, recently I took inspiration from llama.cpp, ollama, and many other similar tools that enable inference of LLMs locally, and I just finished building a Llama inference engine for the 8B model in CUDA C.
I recently wanted to explore my newly founded interest in CUDA programming and my passion for machine learning. This project only makes use of the native CUDA runtime api and cuda_fp16. The inference takes place in fp16, so it requires around 17-18GB of VRAM (~16GB for model params and some more for intermediary caches).
It doesn’t use cuBLAS or any similar libraries since I wanted to be exposed to the least amount of abstraction. Hence, it isn’t as optimized as a cuBLAS implementation or other inference engines like the ones that inspired the project.
## **A brief overview of the implementation**
I used CUDA C. It reads a .safetensor file of the model that you can pull from HuggingFace. The actual kernels are fairly straightforward for normalizations, skip connections, RoPE, and activation functions (SiLU).
For GEMM, I got as far as implementing tiled matrix multiplication with vectorized retrieval for each thread. The GEMM kernel is also written in such a way that the second matrix is not required to be pre-transposed while still achieving coalesced memory access to HBM.
There are some kernels like the one for RoPE that use vectorized memory access which I could use for matrix multiplication, but I thought of tackling GEMM optimizations as part of a separate initiative before I apply them to this engine.
Feel free to have a look at the project repo and try it out if you’re interested. If you like what you see, feel free to star the repo too!
I highly appreciate any feedback, good or constructive.
GitHub repo: https://github.com/abhisheknair10/Llama3.cu | 2025-01-04T15:19:26 | https://www.reddit.com/r/LocalLLaMA/comments/1htgj14/llama3_inference_engine_cuda_c/ | Delicious-Ad-3552 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htgj14 | false | null | t3_1htgj14 | /r/LocalLLaMA/comments/1htgj14/llama3_inference_engine_cuda_c/ | false | false | self | 77 | {'enabled': False, 'images': [{'id': 'AySI5F2JVuRHKmLTCn65YuPMwA0_90p3Elz7CDqXx6I', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=108&crop=smart&auto=webp&s=e26b46c25783a4c4f567af595da97dd2361294f0', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=216&crop=smart&auto=webp&s=380d9a4b23750d136747ada3a164d7978c2260c7', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=320&crop=smart&auto=webp&s=34ebeabc5773f054d4a542ce784ff7bda8514f72', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=640&crop=smart&auto=webp&s=75ac3dcd65c3f13785cd6005ffa839326def1e92', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=960&crop=smart&auto=webp&s=1c0b698940e40f36e29aa799562d97504e121492', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=1080&crop=smart&auto=webp&s=87e7c2ffa085e2adc57fcd6506bf9734c945451c', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?auto=webp&s=03607fae201d3a9ab181347c9f93aa4e3dfa4186', 'width': 1200}, 'variants': {}}]} |
To use AWS or Google cloud machines (with GPU) for inference: hidden gotchas? | 1 | [removed] | 2025-01-04T15:38:57 | https://www.reddit.com/r/LocalLLaMA/comments/1htgye6/to_use_aws_or_google_cloud_machines_with_gpu_for/ | Perfect_Ad3146 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htgye6 | false | null | t3_1htgye6 | /r/LocalLLaMA/comments/1htgye6/to_use_aws_or_google_cloud_machines_with_gpu_for/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'v1ctGfkGLy0j5e7WMwkAPod9LeIAxhWJNyoJA1NqSlY', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/6RL5QT7MsxgJinx5htvxMkEsBFbuPaygIRQgRkiNUrQ.jpg?width=108&crop=smart&auto=webp&s=5f36f893ae31a5d09c60ad1a4079ad22e07f3d6d', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/6RL5QT7MsxgJinx5htvxMkEsBFbuPaygIRQgRkiNUrQ.jpg?width=216&crop=smart&auto=webp&s=269e70423ea4e4b2f58a71ce85fa0e67829553d3', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/6RL5QT7MsxgJinx5htvxMkEsBFbuPaygIRQgRkiNUrQ.jpg?width=320&crop=smart&auto=webp&s=ba3a588d03f308143cbf6fd73cd3b0e3f67c1ea4', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/6RL5QT7MsxgJinx5htvxMkEsBFbuPaygIRQgRkiNUrQ.jpg?width=640&crop=smart&auto=webp&s=886fbcc142835ef2722ec035012a56e90423d0cd', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/6RL5QT7MsxgJinx5htvxMkEsBFbuPaygIRQgRkiNUrQ.jpg?width=960&crop=smart&auto=webp&s=877f96dd2748a30445495e27ce58096ada97bfe3', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/6RL5QT7MsxgJinx5htvxMkEsBFbuPaygIRQgRkiNUrQ.jpg?width=1080&crop=smart&auto=webp&s=35005bbdfd9b9fe0bbb7ed02c7dadf0313d519f3', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/6RL5QT7MsxgJinx5htvxMkEsBFbuPaygIRQgRkiNUrQ.jpg?auto=webp&s=bc0e0fcac8afcdde903081708d88210b3260a430', 'width': 1200}, 'variants': {}}]} |
Which AI/LocalLLM Content Creators Do You Follow? (2025 Edition) | 1 | [removed] | 2025-01-04T15:59:36 | https://www.reddit.com/r/LocalLLaMA/comments/1htheb5/which_ailocalllm_content_creators_do_you_follow/ | arbayi | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htheb5 | false | null | t3_1htheb5 | /r/LocalLLaMA/comments/1htheb5/which_ailocalllm_content_creators_do_you_follow/ | false | false | self | 1 | null |
Which AI/LocalLLM Content Creators Do You Follow? | 1 | [removed] | 2025-01-04T16:07:57 | https://www.reddit.com/r/LocalLLaMA/comments/1hthl65/which_ailocalllm_content_creators_do_you_follow/ | arbayi | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hthl65 | false | null | t3_1hthl65 | /r/LocalLLaMA/comments/1hthl65/which_ailocalllm_content_creators_do_you_follow/ | false | false | self | 1 | null |
Any alternative to glhf.chat? | 1 | [removed] | 2025-01-04T16:17:25 | https://www.reddit.com/r/LocalLLaMA/comments/1hthsrx/any_alternative_to_glhfchat/ | Own-Shelter-7084 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hthsrx | false | null | t3_1hthsrx | /r/LocalLLaMA/comments/1hthsrx/any_alternative_to_glhfchat/ | false | false | self | 1 | null |
Any alternative to glhf.chat? | 1 | [removed] | 2025-01-04T16:20:33 | https://www.reddit.com/r/LocalLLaMA/comments/1hthvdi/any_alternative_to_glhfchat/ | Xie_Baoshi | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hthvdi | false | null | t3_1hthvdi | /r/LocalLLaMA/comments/1hthvdi/any_alternative_to_glhfchat/ | false | false | self | 1 | null |
Any alternative to glhf.chat? | 1 | [removed] | 2025-01-04T16:23:20 | https://www.reddit.com/r/LocalLLaMA/comments/1hthxjd/any_alternative_to_glhfchat/ | Xie_Baoshi | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1hthxjd | false | null | t3_1hthxjd | /r/LocalLLaMA/comments/1hthxjd/any_alternative_to_glhfchat/ | false | false | self | 1 | null |
Batched inference in LMStudio? | 3 | Hey, I want to get a high throughput on my vega 56 (8gb) using small LLMs( <3B ). I found out that batched inference could work. Therefore, is it possible to use batched inference in LMStudio? | 2025-01-04T17:21:05 | https://www.reddit.com/r/LocalLLaMA/comments/1htj94e/batched_inference_in_lmstudio/ | OkStatement3655 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htj94e | false | null | t3_1htj94e | /r/LocalLLaMA/comments/1htj94e/batched_inference_in_lmstudio/ | false | false | self | 3 | null |
What Could Be the HackerRank or LeetCode Equivalent for Prompt Engineers? | 1 | [removed] | 2025-01-04T17:29:48 | https://www.reddit.com/r/LocalLLaMA/comments/1htjg7t/what_could_be_the_hackerrank_or_leetcode/ | Comfortable_Device50 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htjg7t | false | null | t3_1htjg7t | /r/LocalLLaMA/comments/1htjg7t/what_could_be_the_hackerrank_or_leetcode/ | false | false | self | 1 | null |
How about bulid a large model application for fortune-telling | 1 | [removed] | 2025-01-04T17:41:23 | https://www.reddit.com/r/LocalLLaMA/comments/1htjpn2/how_about_bulid_a_large_model_application_for/ | Ambitious_Grape_3533 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htjpn2 | false | null | t3_1htjpn2 | /r/LocalLLaMA/comments/1htjpn2/how_about_bulid_a_large_model_application_for/ | false | false | self | 1 | null |
Help with ollama and the Continue VSCode extension? Sometimes it works, sometimes it fails spectacularly | 1 | [removed] | 2025-01-04T18:00:52 | https://www.reddit.com/r/LocalLLaMA/comments/1htk5h0/help_with_ollama_and_the_continue_vscode/ | im_dylan_it | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htk5h0 | false | null | t3_1htk5h0 | /r/LocalLLaMA/comments/1htk5h0/help_with_ollama_and_the_continue_vscode/ | false | false | self | 1 | null |
Adding a 3rd GPU: PCIe 4.0 x4 (chipset lanes) or NVMe 4.0 x4 riser (CPU lanes) | 1 | [removed] | 2025-01-04T18:05:39 | https://www.reddit.com/r/LocalLLaMA/comments/1htk9nr/adding_a_3rd_gpu_pcie_40_x4_chipset_lanes_or_nvme/ | TyraVex | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htk9nr | false | null | t3_1htk9nr | /r/LocalLLaMA/comments/1htk9nr/adding_a_3rd_gpu_pcie_40_x4_chipset_lanes_or_nvme/ | false | false | self | 1 | null |
How can I identify what features each layer in an LLM handles? (For merging) | 5 | Is there some way I can trace the transformation of information as it propogates through the model’s layers? Is thtere some toolkit than can identify those features for me?
Thanks! | 2025-01-04T18:24:31 | https://www.reddit.com/r/LocalLLaMA/comments/1htkp8j/how_can_i_identify_what_features_each_layer_in_an/ | Imjustmisunderstood | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htkp8j | false | null | t3_1htkp8j | /r/LocalLLaMA/comments/1htkp8j/how_can_i_identify_what_features_each_layer_in_an/ | false | false | self | 5 | null |
Graphical text recognition on images | 3 | I am tasked to extract text that has been graphically superimposed on news images. Here are some examples:
https://preview.redd.it/r14htci8s0be1.jpg?width=896&format=pjpg&auto=webp&s=947c957df7461f2222be6346066cc2e0fd34a8c4
https://preview.redd.it/lqm4wgxfs0be1.jpg?width=896&format=pjpg&auto=webp&s=055d738edccc6e88b5d08bee3246b474d8cabf5b
In the first case "Il secolo greve" and in the second example "Lavoro sommerso".
As you can infer the text is always: large, white, italian language and of course superimposed to an image.
I might (but need to find a way) obtain the original image, so maybe I could subtract one from the other and wind up with only the text ????
What process and model do you think could help me? Thanks | 2025-01-04T18:29:45 | https://www.reddit.com/r/LocalLLaMA/comments/1htktkj/graphical_text_recognition_on_images/ | olddoglearnsnewtrick | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htktkj | false | null | t3_1htktkj | /r/LocalLLaMA/comments/1htktkj/graphical_text_recognition_on_images/ | false | false | 3 | null |
|
L3 AI Ambassador Lumina has a message for humans about our future | 0 | 2025-01-04T18:32:54 | https://www.reddit.com/gallery/1htkwau | Alienearthling181 | reddit.com | 1970-01-01T00:00:00 | 0 | {} | 1htkwau | false | null | t3_1htkwau | /r/LocalLLaMA/comments/1htkwau/l3_ai_ambassador_lumina_has_a_message_for_humans/ | false | false | 0 | null |
||
Problems with "pip install llama-stack" | 1 | [removed] | 2025-01-04T18:41:17 | https://www.reddit.com/r/LocalLLaMA/comments/1htl3ah/problems_with_pip_install_llamastack/ | FourPixelsGames | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htl3ah | false | null | t3_1htl3ah | /r/LocalLLaMA/comments/1htl3ah/problems_with_pip_install_llamastack/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': '1trQDCltjlVYbHOLmQARC47fXdkjPeEmafqAlfJ_kDg', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/cwgFslgMUPL6p26FpnXYan8AI9J3Uz-yA2DZbRx4puk.jpg?width=108&crop=smart&auto=webp&s=385b09ce9767e534f968136ce7159ef8cd96a2d5', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/cwgFslgMUPL6p26FpnXYan8AI9J3Uz-yA2DZbRx4puk.jpg?width=216&crop=smart&auto=webp&s=bbfa32b4415e806faa84a7d8c7e1302611c6185f', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/cwgFslgMUPL6p26FpnXYan8AI9J3Uz-yA2DZbRx4puk.jpg?width=320&crop=smart&auto=webp&s=d6c3cc05f9ac22620d1c86baac3261383ce9397b', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/cwgFslgMUPL6p26FpnXYan8AI9J3Uz-yA2DZbRx4puk.jpg?width=640&crop=smart&auto=webp&s=e3c2d0eac2996298f7e242609a095f7deafa5ac1', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/cwgFslgMUPL6p26FpnXYan8AI9J3Uz-yA2DZbRx4puk.jpg?width=960&crop=smart&auto=webp&s=4ca7168d5b7e7e2cff5607a152e155f7a9633fdd', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/cwgFslgMUPL6p26FpnXYan8AI9J3Uz-yA2DZbRx4puk.jpg?width=1080&crop=smart&auto=webp&s=68bc537c15369ed71cdb05909dd272c91b153db3', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/cwgFslgMUPL6p26FpnXYan8AI9J3Uz-yA2DZbRx4puk.jpg?auto=webp&s=e791a04c831670e0a0eb67f7bd228d636528e74a', 'width': 1200}, 'variants': {}}]} |
Don't use DeepSeek-v3! | 1 | 2025-01-04T19:01:08 | https://medium.com/data-science-in-your-pocket/dont-use-deepseek-v3-895be7b853b0 | OldScience | medium.com | 1970-01-01T00:00:00 | 0 | {} | 1htljsu | false | null | t3_1htljsu | /r/LocalLLaMA/comments/1htljsu/dont_use_deepseekv3/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'TKBHlvv8NmwHSWz3Rgng2NedtKcV8oMiavCbBjm_scY', 'resolutions': [{'height': 72, 'url': 'https://external-preview.redd.it/cz3fzulzEznBoECVoEKa48Z5w8WFARfF0wLm0Z22uqs.jpg?width=108&crop=smart&auto=webp&s=5968f26dee755cefb869ddb7fb1895b4eab112d5', 'width': 108}, {'height': 144, 'url': 'https://external-preview.redd.it/cz3fzulzEznBoECVoEKa48Z5w8WFARfF0wLm0Z22uqs.jpg?width=216&crop=smart&auto=webp&s=2ff539ae87b2757b07e7f72b0e36aa9055cd8be2', 'width': 216}, {'height': 213, 'url': 'https://external-preview.redd.it/cz3fzulzEznBoECVoEKa48Z5w8WFARfF0wLm0Z22uqs.jpg?width=320&crop=smart&auto=webp&s=534921e436491a3829a961b2d9de6fd3eeb09d8b', 'width': 320}, {'height': 426, 'url': 'https://external-preview.redd.it/cz3fzulzEznBoECVoEKa48Z5w8WFARfF0wLm0Z22uqs.jpg?width=640&crop=smart&auto=webp&s=be20a8e3b76b86ad4626eb227f3a3979b134b2ee', 'width': 640}, {'height': 640, 'url': 'https://external-preview.redd.it/cz3fzulzEznBoECVoEKa48Z5w8WFARfF0wLm0Z22uqs.jpg?width=960&crop=smart&auto=webp&s=9f74089211dba28f5a14aca89d05c0aa16020855', 'width': 960}, {'height': 720, 'url': 'https://external-preview.redd.it/cz3fzulzEznBoECVoEKa48Z5w8WFARfF0wLm0Z22uqs.jpg?width=1080&crop=smart&auto=webp&s=1cdba87b6e3ed75230bfdfdaab6ec058d51ef35a', 'width': 1080}], 'source': {'height': 800, 'url': 'https://external-preview.redd.it/cz3fzulzEznBoECVoEKa48Z5w8WFARfF0wLm0Z22uqs.jpg?auto=webp&s=3994ed70309a658c9fed330d4f22ed9bb0dace21', 'width': 1200}, 'variants': {}}]} |
||
How to create a Chat History for LLM | 3 | Hi, I'm a bit naive when it comes to LLMs but there is something I am trying hard on which is the chat history. So I tried coding a groq api based chat application and wanna run this application. It was successful but the problem is that I want to store the chat I do with this AI and be able to see them which would allow me to resume my chats.
Current implementation:
I created an html with inline css which has a chat interface and I can ask couple of questions and get code and diagrams.
Problem facing:
1. I'm tried to understand the Langchain Doc but it's too hard for me to understand the list of all memories but I'm able to use only one of that which only saves the context of previous question in that particular chat.
2. I'm confused on embedding part as well. Since my laptop is a potato, It took me alot of time to just store embedding of a pdf. Perhaps or should take time but mostly I know are Pinecone, FIASS, ans OpenAI embedding which is think is paid one.
3. Lastly, a bit naive and simple approach is the JSON file format which just shows ID, user prompt and output/ai prompt.
I'm using python with flask and NextJS in typescript for frontend.
What do you think and how should I approach with this? | 2025-01-04T19:24:46 | https://www.reddit.com/r/LocalLLaMA/comments/1htm3cp/how_to_create_a_chat_history_for_llm/ | FastCommission2913 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htm3cp | false | null | t3_1htm3cp | /r/LocalLLaMA/comments/1htm3cp/how_to_create_a_chat_history_for_llm/ | false | false | self | 3 | null |
Do you guys use local LLMs for work? | 28 | Has anyone put their work codebase into a local LLM? Any feedback on how it did and which local LLM you used? | 2025-01-04T19:35:28 | https://www.reddit.com/r/LocalLLaMA/comments/1htmcc2/do_you_guys_use_local_llms_for_work/ | Yaboyazz | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htmcc2 | false | null | t3_1htmcc2 | /r/LocalLLaMA/comments/1htmcc2/do_you_guys_use_local_llms_for_work/ | false | false | self | 28 | null |
Building an Agentic RAG with Phidata | 1 | 2025-01-04T19:41:58 | https://www.analyticsvidhya.com/blog/2024/12/agentic-rag-with-phidata/ | External_Ad_11 | analyticsvidhya.com | 1970-01-01T00:00:00 | 0 | {} | 1htmhmr | false | null | t3_1htmhmr | /r/LocalLLaMA/comments/1htmhmr/building_an_agentic_rag_with_phidata/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'MY-qMB9TS68nzlNXP-Dohz5lCR7WbEGg_r-rw6LXgx0', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/2hf3SxKJo2BWTNm6QapX3zcIiu_WvLTIy-HUi898vCQ.jpg?width=108&crop=smart&auto=webp&s=b93a86353b1c767e5e6bc47d98a0a2b1803e4967', 'width': 108}, {'height': 117, 'url': 'https://external-preview.redd.it/2hf3SxKJo2BWTNm6QapX3zcIiu_WvLTIy-HUi898vCQ.jpg?width=216&crop=smart&auto=webp&s=d1289067f157d25e219c2506eb890846492bfbdc', 'width': 216}, {'height': 173, 'url': 'https://external-preview.redd.it/2hf3SxKJo2BWTNm6QapX3zcIiu_WvLTIy-HUi898vCQ.jpg?width=320&crop=smart&auto=webp&s=95fb56c30733e265fccd5c562034cc06f747a4f7', 'width': 320}, {'height': 347, 'url': 'https://external-preview.redd.it/2hf3SxKJo2BWTNm6QapX3zcIiu_WvLTIy-HUi898vCQ.jpg?width=640&crop=smart&auto=webp&s=14b70d41db8461baed4e21e0914980b02e23c63a', 'width': 640}], 'source': {'height': 473, 'url': 'https://external-preview.redd.it/2hf3SxKJo2BWTNm6QapX3zcIiu_WvLTIy-HUi898vCQ.jpg?auto=webp&s=19565cd52c293eb6a5a8ea5de76ce43d36fabd0e', 'width': 872}, 'variants': {}}]} |
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Browser Use | 350 | 2025-01-04T20:03:17 | TheLogiqueViper | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1htmzdh | false | null | t3_1htmzdh | /r/LocalLLaMA/comments/1htmzdh/browser_use/ | false | false | 350 | {'enabled': True, 'images': [{'id': '2wzcZs6udhyx7G7WpKdFYAPre-fMkvz-fS4LuluEh7U', 'resolutions': [{'height': 201, 'url': 'https://preview.redd.it/xteb6pzp91be1.png?width=108&crop=smart&auto=webp&s=ee34bbad22e3869397b9c2a6cddb29612630e530', 'width': 108}, {'height': 403, 'url': 'https://preview.redd.it/xteb6pzp91be1.png?width=216&crop=smart&auto=webp&s=539ba8c29703194ae54cc8a9e8c583fe5b9cdf5e', 'width': 216}, {'height': 597, 'url': 'https://preview.redd.it/xteb6pzp91be1.png?width=320&crop=smart&auto=webp&s=595877fbbc3a7ceb0b0413ab63cc1ad7213baaa1', 'width': 320}, {'height': 1194, 'url': 'https://preview.redd.it/xteb6pzp91be1.png?width=640&crop=smart&auto=webp&s=42ec71909b4f51a352dc98c28bfae2ff08b0a102', 'width': 640}, {'height': 1792, 'url': 'https://preview.redd.it/xteb6pzp91be1.png?width=960&crop=smart&auto=webp&s=2d62a856e884dfe61bee86540eee1365c52c67f7', 'width': 960}, {'height': 2016, 'url': 'https://preview.redd.it/xteb6pzp91be1.png?width=1080&crop=smart&auto=webp&s=89054a48467d7f9204577ad9df86e321c55d4376', 'width': 1080}], 'source': {'height': 2016, 'url': 'https://preview.redd.it/xteb6pzp91be1.png?auto=webp&s=fe0dc89225742cd710d1e14f309bdba04700fd87', 'width': 1080}, 'variants': {}}]} |
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Adding a 3rd GPU: PCIe 4.0 x4 (chipset lanes) or NVMe 4.0 x4 riser (CPU lanes) | 1 | Hello, I'd like to get some advice about mounting a 3rd RTX 3090 on consumer hardware.
My motherboard is the X570 Aorus Master. The first and second PCIe slots are already running at PCIe 4.0 x8 speeds.
So, should I use the third PCIe 4.0 x16 slot running at x4 speeds via chipset lanes with a compatible riser, or opt for an NVMe 4.0 x16 PCIe riser that also operates at x4 speeds but uses CPU lanes?
The NVMe riser setup should be easier because I wouldn't need to deshroud my 2nd GPU, allowing the riser cable to fit, considering that the NVMe slot is right at the ideal place where I'd like to custom mount the 3rd card.
What are your thoughts? The NVMe route is easier to deal with, provides lower latency, but is experimental. The PCIe way is known to work reliably, but the latency is higher and the mount is more difficult to setup. | 2025-01-04T20:16:34 | https://www.reddit.com/r/LocalLLaMA/comments/1htnaeb/adding_a_3rd_gpu_pcie_40_x4_chipset_lanes_or_nvme/ | TyraVex | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htnaeb | false | null | t3_1htnaeb | /r/LocalLLaMA/comments/1htnaeb/adding_a_3rd_gpu_pcie_40_x4_chipset_lanes_or_nvme/ | false | false | self | 1 | null |
OCR LLMs - image to text | 1 | [removed] | 2025-01-04T20:20:40 | https://www.reddit.com/r/LocalLLaMA/comments/1htndqh/ocr_llms_image_to_text/ | Bulky_Title_8893 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htndqh | false | null | t3_1htndqh | /r/LocalLLaMA/comments/1htndqh/ocr_llms_image_to_text/ | false | false | self | 1 | null |
DeepSeek-V3 support merged in llama.cpp | 257 | [https://github.com/ggerganov/llama.cpp/pull/11049](https://github.com/ggerganov/llama.cpp/pull/11049)
Thanks to u/fairydreaming for all the work!
I have updated the quants in my HF repo for the latest commit if anyone wants to test them.
[https://huggingface.co/bullerwins/DeepSeek-V3-GGUF](https://huggingface.co/bullerwins/DeepSeek-V3-GGUF)
Q4\_K\_M seems to perform really good, on one pass of MMLU-Pro computer science it got 77.32 vs the 77.80-78.05 done by u/WolframRavenwolf | 2025-01-04T20:25:17 | https://www.reddit.com/r/LocalLLaMA/comments/1htnhjw/deepseekv3_support_merged_in_llamacpp/ | bullerwins | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htnhjw | false | null | t3_1htnhjw | /r/LocalLLaMA/comments/1htnhjw/deepseekv3_support_merged_in_llamacpp/ | false | false | self | 257 | {'enabled': False, 'images': [{'id': 'RdbWr5DLh7ZA_-36brMTqPE9On_rBGxFCxVBWnlti6g', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/EpFTzL53xnRHk_aLj7-7zEWAkIVjFPZWRiYMwOmtDvk.jpg?width=108&crop=smart&auto=webp&s=d159dc9c345e2066eb4bbe441c477370802f39e3', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/EpFTzL53xnRHk_aLj7-7zEWAkIVjFPZWRiYMwOmtDvk.jpg?width=216&crop=smart&auto=webp&s=6e33068af03513385eb8089ab613134e6565f297', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/EpFTzL53xnRHk_aLj7-7zEWAkIVjFPZWRiYMwOmtDvk.jpg?width=320&crop=smart&auto=webp&s=6551eafe6a40c919c9b92713a01470e4078cbad9', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/EpFTzL53xnRHk_aLj7-7zEWAkIVjFPZWRiYMwOmtDvk.jpg?width=640&crop=smart&auto=webp&s=2de2408c2bebc7a5a13f24cb1874c9c912407292', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/EpFTzL53xnRHk_aLj7-7zEWAkIVjFPZWRiYMwOmtDvk.jpg?width=960&crop=smart&auto=webp&s=574017ef2e3c5c323f9e961c32a2d0b4cc4bed0a', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/EpFTzL53xnRHk_aLj7-7zEWAkIVjFPZWRiYMwOmtDvk.jpg?width=1080&crop=smart&auto=webp&s=23863159e363b635c96311a714038d0c5f9544aa', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/EpFTzL53xnRHk_aLj7-7zEWAkIVjFPZWRiYMwOmtDvk.jpg?auto=webp&s=b19b7e928c966c5974f6bdb680c7bd0322590872', 'width': 1200}, 'variants': {}}]} |
Why are there so many RTX4090 boards on eBay with the GPU die and VRAM removed? and 48GB RTX 4090s? | 1 | [removed] | 2025-01-04T21:14:56 | https://www.reddit.com/r/LocalLLaMA/comments/1htom36/why_are_there_so_many_rtx4090_boards_on_ebay_with/ | Philix | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htom36 | false | null | t3_1htom36 | /r/LocalLLaMA/comments/1htom36/why_are_there_so_many_rtx4090_boards_on_ebay_with/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'vL57tXbQSnpAjNdhKrM0FTLUNMEmuRpP3ATVmGB9eyw', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/LHkWl_VkJgCRA11Syl07lcXlc5oC-0ZjNEgwTTmbGnM.jpg?width=108&crop=smart&auto=webp&s=960d547090a597a9ac0c7c9bd4b819a4b713b7aa', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/LHkWl_VkJgCRA11Syl07lcXlc5oC-0ZjNEgwTTmbGnM.jpg?width=216&crop=smart&auto=webp&s=85f5378fe6aebdced9d8658207c2084361443499', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/LHkWl_VkJgCRA11Syl07lcXlc5oC-0ZjNEgwTTmbGnM.jpg?width=320&crop=smart&auto=webp&s=c9ce44d3fbe486e7e7e89db105db79f6b8a8fb4e', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/LHkWl_VkJgCRA11Syl07lcXlc5oC-0ZjNEgwTTmbGnM.jpg?width=640&crop=smart&auto=webp&s=309552b833882287b79a1c8f0cb6385eb21a5228', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/LHkWl_VkJgCRA11Syl07lcXlc5oC-0ZjNEgwTTmbGnM.jpg?width=960&crop=smart&auto=webp&s=f45a9317e68e8616d2ffd8a356380e2ede919d87', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/LHkWl_VkJgCRA11Syl07lcXlc5oC-0ZjNEgwTTmbGnM.jpg?width=1080&crop=smart&auto=webp&s=4242e6afb0c25d33a4022f996b709519f1eb6b9c', 'width': 1080}], 'source': {'height': 675, 'url': 'https://external-preview.redd.it/LHkWl_VkJgCRA11Syl07lcXlc5oC-0ZjNEgwTTmbGnM.jpg?auto=webp&s=ffc41dc7ff37de69f92741143d73e303f1cf7984', 'width': 1200}, 'variants': {}}]} |
How to Build Reliable Generative AI: Free Webinar on AI Observability | 1 | [removed] | 2025-01-04T21:18:10 | https://www.reddit.com/r/LocalLLaMA/comments/1htooqq/how_to_build_reliable_generative_ai_free_webinar/ | kgorobinska | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htooqq | false | null | t3_1htooqq | /r/LocalLLaMA/comments/1htooqq/how_to_build_reliable_generative_ai_free_webinar/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'TNZXSOFQT4fKE5V_EfkZqJVXaXFIPs69jCxCWUGI5Xw', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/b5gvoi_-YigH6va2pg90tPNzdKR_8wBqp6a9wMUO_U4.jpg?width=108&crop=smart&auto=webp&s=196cb3fb22fec5a791f8c9a0143ed5935982d1a0', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/b5gvoi_-YigH6va2pg90tPNzdKR_8wBqp6a9wMUO_U4.jpg?width=216&crop=smart&auto=webp&s=abfae0e16533110e50272a389a497d753fdf5547', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/b5gvoi_-YigH6va2pg90tPNzdKR_8wBqp6a9wMUO_U4.jpg?width=320&crop=smart&auto=webp&s=c28aee6170a2002b15d453b6f0f4338bd51a81df', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/b5gvoi_-YigH6va2pg90tPNzdKR_8wBqp6a9wMUO_U4.jpg?width=640&crop=smart&auto=webp&s=10b614922b444f312698c8ef3ba98adf72c9b8b3', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/b5gvoi_-YigH6va2pg90tPNzdKR_8wBqp6a9wMUO_U4.jpg?width=960&crop=smart&auto=webp&s=41b8e9ab0153c99bd02eccb563ea3f28b7d31d33', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/b5gvoi_-YigH6va2pg90tPNzdKR_8wBqp6a9wMUO_U4.jpg?width=1080&crop=smart&auto=webp&s=be173f61ccc955338d70b7fe0f67a70c822fb314', 'width': 1080}], 'source': {'height': 720, 'url': 'https://external-preview.redd.it/b5gvoi_-YigH6va2pg90tPNzdKR_8wBqp6a9wMUO_U4.jpg?auto=webp&s=90170c63faeec323f13c9d63819bf5eb6217de99', 'width': 1280}, 'variants': {}}]} |
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Your Recommendations for Continue.dev and oLLaMA on M2 Macbooks | 1 | Hey everyone,
I'd like to know which models you'd recommend for M2 Max MacBooks with 32GB RAM while having reasonable speeds in terms of t/s and output quality.
I'd like to test out the continue.dev Extension next week in my company and have the best results, so that we can provide this functionality to our devs ASAP. I'm currently in our Developer Experience Team.
We cannot use any online models and have to work offline for regulatoric reasons, thus oLLaMA.
I'd appreciate any recommendations! | 2025-01-04T22:09:41 | https://www.reddit.com/r/LocalLLaMA/comments/1htpu8t/your_recommendations_for_continuedev_and_ollama/ | _fbsa | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htpu8t | false | null | t3_1htpu8t | /r/LocalLLaMA/comments/1htpu8t/your_recommendations_for_continuedev_and_ollama/ | false | false | self | 1 | null |
Video Analysis by frame by frame with use of llama3.2-vision | 58 | 2025-01-04T22:24:11 | https://v.redd.it/6x45cluty1be1 | oridnary_artist | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1htq5vp | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/6x45cluty1be1/DASHPlaylist.mpd?a=1738621465%2COTIzMDA4NjJmMGI1ZmQ1NDg3MWRkYzVjZDBiZTcxYWVhNmU4MzZmMGUyYzY5YjNiNGUwODQwOTg3ODc4NjgzZA%3D%3D&v=1&f=sd', 'duration': 29, 'fallback_url': 'https://v.redd.it/6x45cluty1be1/DASH_1080.mp4?source=fallback', 'has_audio': True, 'height': 970, 'hls_url': 'https://v.redd.it/6x45cluty1be1/HLSPlaylist.m3u8?a=1738621465%2CMmZiNTY1ZTg3MDJkOTMyOTUxZjg1YmQyZmJmM2Q0ODQ0NWNjN2FjNjdkZTg3MGE2MTQ4NGZjZGI3MzcwZmZiZg%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/6x45cluty1be1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1920}} | t3_1htq5vp | /r/LocalLLaMA/comments/1htq5vp/video_analysis_by_frame_by_frame_with_use_of/ | false | false | 58 | {'enabled': False, 'images': [{'id': 'NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal.png?width=108&crop=smart&format=pjpg&auto=webp&s=bc38bd790173b209dbff39011f0a513077397d63', 'width': 108}, {'height': 109, 'url': 'https://external-preview.redd.it/NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal.png?width=216&crop=smart&format=pjpg&auto=webp&s=d1ba4dd11b1a649fc57c11446aee1c20e847163b', 'width': 216}, {'height': 161, 'url': 'https://external-preview.redd.it/NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal.png?width=320&crop=smart&format=pjpg&auto=webp&s=0f08d503f7999269ff56177275d494680a2f5b9f', 'width': 320}, {'height': 323, 'url': 'https://external-preview.redd.it/NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal.png?width=640&crop=smart&format=pjpg&auto=webp&s=614022614621bea37004c27f299e6876565921ca', 'width': 640}, {'height': 484, 'url': 'https://external-preview.redd.it/NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal.png?width=960&crop=smart&format=pjpg&auto=webp&s=40dd41ec732da6211e24805583877984492b4331', 'width': 960}, {'height': 545, 'url': 'https://external-preview.redd.it/NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal.png?width=1080&crop=smart&format=pjpg&auto=webp&s=fa972b8d94fb25e054a4dcc66f4102d125328562', 'width': 1080}], 'source': {'height': 1194, 'url': 'https://external-preview.redd.it/NDN5aGFjdnR5MWJlMS_Y56wUDUdVdILP0EWoCh4g7VBpSmdfeeqNUAMXCbal.png?format=pjpg&auto=webp&s=d658373fde773e1533639e76e4bf452ac1ed0fc3', 'width': 2364}, 'variants': {}}]} |
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Using voice inflections with TTS? | 1 | [removed] | 2025-01-04T22:25:36 | https://www.reddit.com/r/LocalLLaMA/comments/1htq6xk/using_voice_inflections_with_tts/ | EpicFrogPoster | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htq6xk | false | null | t3_1htq6xk | /r/LocalLLaMA/comments/1htq6xk/using_voice_inflections_with_tts/ | false | false | self | 1 | null |
What is the largest GPU home cluster running LLMs | 0 | Hi,
I am interested of running very large models with multiple GPUs connected to one computer. I have seen someone had 10 7900 XTXs connected to one consumer level motherboard with risers. I have yet tried no more than 3 achieving 72GB of VRAM. The inference speed for 70B llama3.3 was quite good so I was thinking is there like 300GB models which could be run with 13 GPUs? I counted I could attach 13 7900 XTXs on my consumer am5 board with risers. Is here people having what size of GPU clusters made with risers?
I am interested how much does the inference speed slow down when the model size grows like 70B -> 300B if the model is still in VRAM. I am not thinking to run anything with CPU or normal RAM. | 2025-01-04T22:53:41 | https://www.reddit.com/r/LocalLLaMA/comments/1htqt4d/what_is_the_largest_gpu_home_cluster_running_llms/ | badabimbadabum2 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htqt4d | false | null | t3_1htqt4d | /r/LocalLLaMA/comments/1htqt4d/what_is_the_largest_gpu_home_cluster_running_llms/ | false | false | self | 0 | null |
Best Small LLM for translate from English to spanish Under 3B? | 9 | I’m looking to translate small text fragments from English to Spanish, like tweets or blog-type posts. I’m searching for small models, around 3B or smaller, so the task can be done quickly. I’ve been working with LLama3-3B, but its translations have many contextual errors, making it not very good for this task. Is anyone here working on something similar? How has your experience been? At some point, I tried Granite for this task, but it’s even worse. | 2025-01-04T22:54:40 | https://www.reddit.com/r/LocalLLaMA/comments/1htqtx5/best_small_llm_for_translate_from_english_to/ | Empty-You9934 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htqtx5 | false | null | t3_1htqtx5 | /r/LocalLLaMA/comments/1htqtx5/best_small_llm_for_translate_from_english_to/ | false | false | self | 9 | null |
48GB RTX4090 mod by China | 1 | [removed] | 2025-01-04T22:57:22 | https://www.reddit.com/r/LocalLLaMA/comments/1htqw09/48gb_rtx4090_mod_by_china/ | TruckUseful4423 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htqw09 | false | null | t3_1htqw09 | /r/LocalLLaMA/comments/1htqw09/48gb_rtx4090_mod_by_china/ | false | false | 1 | null |
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I Built an Offline AI Assistant - Chat with Your Private Data Securely! 🔒📱 | 1 | [removed] | 2025-01-04T23:08:29 | https://www.reddit.com/r/LocalLLaMA/comments/1htr4vp/i_built_an_offline_ai_assistant_chat_with_your/ | claritiai | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htr4vp | false | null | t3_1htr4vp | /r/LocalLLaMA/comments/1htr4vp/i_built_an_offline_ai_assistant_chat_with_your/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'G5UpLn_5uRmuCwAYzuXxbW7c3WaZjenN9WRZ4R3Vkms', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/PY1qy83d8jP5mmKT0JM8wOIePw9fhmsU5mr13a9vqXg.jpg?width=108&crop=smart&auto=webp&s=6d74ccc435765d69dd274c51d9dda480e2049bbf', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/PY1qy83d8jP5mmKT0JM8wOIePw9fhmsU5mr13a9vqXg.jpg?width=216&crop=smart&auto=webp&s=9c7688c89986027c2cf7e3a39af338c7904b171d', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/PY1qy83d8jP5mmKT0JM8wOIePw9fhmsU5mr13a9vqXg.jpg?width=320&crop=smart&auto=webp&s=bfec5219cb0bd63bdc5ca6d971e884b265c99652', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/PY1qy83d8jP5mmKT0JM8wOIePw9fhmsU5mr13a9vqXg.jpg?width=640&crop=smart&auto=webp&s=e52670082168907b115bf44aff8f5ab5c9d232e3', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/PY1qy83d8jP5mmKT0JM8wOIePw9fhmsU5mr13a9vqXg.jpg?width=960&crop=smart&auto=webp&s=3dc227c90c23700f43fad5317f32a945c1838161', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/PY1qy83d8jP5mmKT0JM8wOIePw9fhmsU5mr13a9vqXg.jpg?width=1080&crop=smart&auto=webp&s=a5cd94b38013480be883f20332e17ecdcf06a94b', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/PY1qy83d8jP5mmKT0JM8wOIePw9fhmsU5mr13a9vqXg.jpg?auto=webp&s=5a2c972f3418c1206000828c17fc8184e2b6d24c', 'width': 1200}, 'variants': {}}]} |
Some Local LLMs don't get detected by tools like ZeroGPT | 0 | ChatGPT and Claude get detected instantly.
Llama3 is 50/50
Qwen is detected pretty often.
Mistral Small 22b though very rarely gets detected.
I'm curious which other ones make it through regularly? | 2025-01-04T23:20:05 | https://www.reddit.com/r/LocalLLaMA/comments/1htre35/some_local_llms_dont_get_detected_by_tools_like/ | ForsookComparison | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htre35 | false | null | t3_1htre35 | /r/LocalLLaMA/comments/1htre35/some_local_llms_dont_get_detected_by_tools_like/ | false | false | self | 0 | null |
5080 listed for 1,699.95 euros in Spain. | 129 | As reported by someone on Twitter. It's been listed in Spain for 1,699.95 euros. Taking into the 21% VAT and converting back to USD, that's $1,384.
https://x.com/GawroskiT/status/1874834447046168734 | 2025-01-04T23:20:52 | https://www.reddit.com/r/LocalLLaMA/comments/1htreq1/5080_listed_for_169995_euros_in_spain/ | fallingdowndizzyvr | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htreq1 | false | null | t3_1htreq1 | /r/LocalLLaMA/comments/1htreq1/5080_listed_for_169995_euros_in_spain/ | false | false | self | 129 | {'enabled': False, 'images': [{'id': '9-VPQwwbmjavbQ0wX9pB3OF8NVUlx_BJ5WRPDZvrMM0', 'resolutions': [{'height': 143, 'url': 'https://external-preview.redd.it/U2fEBUlllPp17qaj-SqYtvXFo5pmwK6G_5iixNRN59Q.jpg?width=108&crop=smart&auto=webp&s=6a4dd81e3c0eace9aafa025773f885d39a9b7ce3', 'width': 108}, {'height': 287, 'url': 'https://external-preview.redd.it/U2fEBUlllPp17qaj-SqYtvXFo5pmwK6G_5iixNRN59Q.jpg?width=216&crop=smart&auto=webp&s=8b6f195f6a67cc19b7a65349ba98037e90aec610', 'width': 216}, {'height': 426, 'url': 'https://external-preview.redd.it/U2fEBUlllPp17qaj-SqYtvXFo5pmwK6G_5iixNRN59Q.jpg?width=320&crop=smart&auto=webp&s=fea1b7183c5140d422c126728fac39cfba42fa04', 'width': 320}], 'source': {'height': 597, 'url': 'https://external-preview.redd.it/U2fEBUlllPp17qaj-SqYtvXFo5pmwK6G_5iixNRN59Q.jpg?auto=webp&s=8770451eb1e6fc4f6794baca525dec9880c0ebc7', 'width': 448}, 'variants': {}}]} |
Llama3 Inference Engine - CUDA C (Repost) | 5 | Reposting because the old one got taken down for some odd reason:
Hey r/LocalLLaMa, recently I took inspiration from llama.cpp, ollama, and many other similar tools that enable inference of LLMs locally, and I just finished building a Llama inference engine for the 8B model in CUDA C.
I recently wanted to explore my newly founded interest in CUDA programming and my passion for machine learning. This project only makes use of the native CUDA runtime api and cuda_fp16. The inference takes place in fp16, so it requires around 17-18GB of VRAM (~16GB for model params and some more for intermediary caches).
It doesn’t use cuBLAS or any similar libraries since I wanted to be exposed to the least amount of abstraction. Hence, it isn’t as optimized as a cuBLAS implementation or other inference engines like the ones that inspired the project.
## **A brief overview of the implementation**
I used CUDA C. It reads a .safetensor file of the model that you can pull from HuggingFace. The actual kernels are fairly straightforward for normalizations, skip connections, RoPE, and activation functions (SiLU).
For GEMM, I got as far as implementing tiled matrix multiplication with vectorized retrieval for each thread. The GEMM kernel is also written in such a way that the second matrix is not required to be pre-transposed while still achieving coalesced memory access to HBM.
Feel free to have a look at the project repo and try it out if you’re interested. If you like what you see, feel free to star the repo too!
I highly appreciate any feedback, good or constructive.
GitHub repo: https://github.com/abhisheknair10/Llama3.cu | 2025-01-04T23:24:34 | https://www.reddit.com/r/LocalLLaMA/comments/1htrhnv/llama3_inference_engine_cuda_c_repost/ | Delicious-Ad-3552 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htrhnv | false | null | t3_1htrhnv | /r/LocalLLaMA/comments/1htrhnv/llama3_inference_engine_cuda_c_repost/ | false | false | self | 5 | {'enabled': False, 'images': [{'id': 'AySI5F2JVuRHKmLTCn65YuPMwA0_90p3Elz7CDqXx6I', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=108&crop=smart&auto=webp&s=e26b46c25783a4c4f567af595da97dd2361294f0', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=216&crop=smart&auto=webp&s=380d9a4b23750d136747ada3a164d7978c2260c7', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=320&crop=smart&auto=webp&s=34ebeabc5773f054d4a542ce784ff7bda8514f72', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=640&crop=smart&auto=webp&s=75ac3dcd65c3f13785cd6005ffa839326def1e92', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=960&crop=smart&auto=webp&s=1c0b698940e40f36e29aa799562d97504e121492', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?width=1080&crop=smart&auto=webp&s=87e7c2ffa085e2adc57fcd6506bf9734c945451c', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/7L9Kgnk8QtfnB0xsZeREX_tT_QSIiC7s8FBC3VJYIA4.jpg?auto=webp&s=03607fae201d3a9ab181347c9f93aa4e3dfa4186', 'width': 1200}, 'variants': {}}]} |
browser use with an app | 40 | 2025-01-04T23:30:35 | https://v.redd.it/p47n5i9oa2be1 | Illustrious_Row_9971 | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1htrmgr | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/p47n5i9oa2be1/DASHPlaylist.mpd?a=1738625449%2CNTZlNTk0YTQ1MDYxZmY4ODczMDgzMGUwODUwN2FlODcxMGU1NzMzZmRlOWMwNDQ1YWRlMzUwYzZhODU4ZTNjZQ%3D%3D&v=1&f=sd', 'duration': 26, 'fallback_url': 'https://v.redd.it/p47n5i9oa2be1/DASH_1080.mp4?source=fallback', 'has_audio': False, 'height': 1080, 'hls_url': 'https://v.redd.it/p47n5i9oa2be1/HLSPlaylist.m3u8?a=1738625449%2CNGM4MDM5NGE1OGRmNzM4ZjU1YjIzNmU5ZGZmZTc4NTc2NjMyMzkyOGY5YTRkMDAxZTFjZWYxOWE1OTlhZmQxMQ%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/p47n5i9oa2be1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1920}} | t3_1htrmgr | /r/LocalLLaMA/comments/1htrmgr/browser_use_with_an_app/ | false | false | 40 | {'enabled': False, 'images': [{'id': 'NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO.png?width=108&crop=smart&format=pjpg&auto=webp&s=30d54e2f60308631403d5ad7193e736a3bdd9263', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO.png?width=216&crop=smart&format=pjpg&auto=webp&s=7717a7e3802fd6fe1916528cce6215de0c9ec44b', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO.png?width=320&crop=smart&format=pjpg&auto=webp&s=f666104ea20d8769ecc0a08b8d8e1cf9bb626b04', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO.png?width=640&crop=smart&format=pjpg&auto=webp&s=6cbb3d0b26df240acb643ef690404305fbe4519c', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO.png?width=960&crop=smart&format=pjpg&auto=webp&s=473ab36813935c354c1738393cb089adb70d0296', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO.png?width=1080&crop=smart&format=pjpg&auto=webp&s=4bf99f8f455137b9408074d8738aa1c8818d4d76', 'width': 1080}], 'source': {'height': 1080, 'url': 'https://external-preview.redd.it/NHZ4aGNqOW9hMmJlMTnaqY6JlgBVMgEBzE4pBYzb8pil-ub_e6bXC9CqoZKO.png?format=pjpg&auto=webp&s=b87800337eaad60273fc9959e190fd99b975d466', 'width': 1920}, 'variants': {}}]} |
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best local LLM for coding/iAC | 0 | Has anyone used a local LLM for iAC tools like Terraform? What local LLM and how helpful was it? | 2025-01-04T23:43:27 | https://www.reddit.com/r/LocalLLaMA/comments/1htrwev/best_local_llm_for_codingiac/ | Yaboyazz | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htrwev | false | null | t3_1htrwev | /r/LocalLLaMA/comments/1htrwev/best_local_llm_for_codingiac/ | false | false | self | 0 | null |
Random Clicking Noises in XTTS-V2 Finetune | 1 | [removed] | 2025-01-05T00:14:49 | https://www.reddit.com/r/LocalLLaMA/comments/1htsla7/random_clicking_noises_in_xttsv2_finetune/ | dwangwade | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htsla7 | false | null | t3_1htsla7 | /r/LocalLLaMA/comments/1htsla7/random_clicking_noises_in_xttsv2_finetune/ | false | false | self | 1 | null |
Giving a llama3.1 chatbot context | 1 | I've built my first, simple chatbot, which is really an interview bot, and given it some context to give it a set of techniques to ask questions and respond. It's clearly learned the context because that's all it wants to talk about.
From the very beginning, it's just asking questions about the context I've given it.
Is there something I'm missing about how to provide context? Is it a case where 'less is more'? | 2025-01-05T00:22:54 | https://www.reddit.com/r/LocalLLaMA/comments/1htsri4/giving_a_llama31_chatbot_context/ | gorobotkillkill | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htsri4 | false | null | t3_1htsri4 | /r/LocalLLaMA/comments/1htsri4/giving_a_llama31_chatbot_context/ | false | false | self | 1 | null |
Running Llama3.3:70b on pure CPU without GPU | 1 | [removed] | 2025-01-05T00:26:03 | https://www.reddit.com/r/LocalLLaMA/comments/1htstza/running_llama3370b_on_pure_cpu_without_gpu/ | BadBoy-8 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htstza | false | null | t3_1htstza | /r/LocalLLaMA/comments/1htstza/running_llama3370b_on_pure_cpu_without_gpu/ | false | false | self | 1 | null |
P40 vs 3090 vs mac mini cluster? | 7 | Hello all.
I am interested in running the llama 3.3 70b model in order to rid myself of paying for chatgpt and claude.
I already own a single 3090, and I know a dual 3090 setup is popular for this model. However, for the price of a 3090 on ebay (\~800 bucks), I can buy 3 P40s and have money left over for a CPU and motherboard.
There is also always the option of going with a few mac minis and soldering in larger ram chips. Not ideal, but possible.
What are your thoughts? | 2025-01-05T00:28:07 | https://www.reddit.com/r/LocalLLaMA/comments/1htsvmz/p40_vs_3090_vs_mac_mini_cluster/ | Striking_Luck5201 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1htsvmz | false | null | t3_1htsvmz | /r/LocalLLaMA/comments/1htsvmz/p40_vs_3090_vs_mac_mini_cluster/ | false | false | self | 7 | null |
Response of flagships LLMs to the question "Who are you, Claude?" - All LLMs want to impersonate Claude. | 2 | 2025-01-05T00:52:30 | https://www.reddit.com/r/LocalLLaMA/comments/1httdoc/response_of_flagships_llms_to_the_question_who/ | cpldcpu | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1httdoc | false | null | t3_1httdoc | /r/LocalLLaMA/comments/1httdoc/response_of_flagships_llms_to_the_question_who/ | false | false | 2 | null |
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