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Hugging Face added Text to SQL on all 250K+ Public Datasets - powered by Qwen 2.5 Coder 32B 🔥 | 161 | 2024-12-02T14:27:09 | https://v.redd.it/e3t9ae0h3g4e1 | vaibhavs10 | /r/LocalLLaMA/comments/1h4w5a3/hugging_face_added_text_to_sql_on_all_250k_public/ | 1970-01-01T00:00:00 | 0 | {} | 1h4w5a3 | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/e3t9ae0h3g4e1/DASHPlaylist.mpd?a=1735871809%2COTkyNGYyNjRlNDE0YjA5ZThhMjhkZGNlNzliYTE2NjEwZmM1NzUyOTM2ZDRlZmIxMzhmZTFkOGU3MTNiYjYyOA%3D%3D&v=1&f=sd', 'duration': 32, 'fallback_url': 'https://v.redd.it/e3t9ae0h3g4e1/DASH_1080.mp4?source=fallback', 'has_audio': False, 'height': 1080, 'hls_url': 'https://v.redd.it/e3t9ae0h3g4e1/HLSPlaylist.m3u8?a=1735871809%2CMzRkOGI1ZDNkZGNiZTI5ZmI2NzBhMzk5MmFiYjczMmM4MWE0NWM2M2Y1ZmIwNDZjNmMxOGRhMjQzYmQ2OWJiZg%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/e3t9ae0h3g4e1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1728}} | t3_1h4w5a3 | /r/LocalLLaMA/comments/1h4w5a3/hugging_face_added_text_to_sql_on_all_250k_public/ | false | false | 161 | {'enabled': False, 'images': [{'id': 'eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T', 'resolutions': [{'height': 67, 'url': 'https://external-preview.redd.it/eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T.png?width=108&crop=smart&format=pjpg&auto=webp&s=25e8ff37ce636ae7097d01221c72af123280ff9b', 'width': 108}, {'height': 135, 'url': 'https://external-preview.redd.it/eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T.png?width=216&crop=smart&format=pjpg&auto=webp&s=c4bf9220d38512b3f2a95605cdcac3e5a8bfa12a', 'width': 216}, {'height': 200, 'url': 'https://external-preview.redd.it/eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T.png?width=320&crop=smart&format=pjpg&auto=webp&s=1e116024d5c48f69698f6674ca6fbba816a52c18', 'width': 320}, {'height': 400, 'url': 'https://external-preview.redd.it/eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T.png?width=640&crop=smart&format=pjpg&auto=webp&s=794ab9d4bfcabd6046369fba87771f89490b9ede', 'width': 640}, {'height': 600, 'url': 'https://external-preview.redd.it/eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T.png?width=960&crop=smart&format=pjpg&auto=webp&s=9f2dffb6615ffee96d8e017b39ddeba1cdc524ed', 'width': 960}, {'height': 675, 'url': 'https://external-preview.redd.it/eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T.png?width=1080&crop=smart&format=pjpg&auto=webp&s=7ad29b71bd33fd8bbbabc338f38b03d16a98ba67', 'width': 1080}], 'source': {'height': 1800, 'url': 'https://external-preview.redd.it/eHh1dmMyZW8zZzRlMZTAGrkeLZO1tBuiimB5X60UvGnb2VnYDJyVQ1Os4m4T.png?format=pjpg&auto=webp&s=d60555ee66d010fac17c6e9bd93f4a5156543f8f', 'width': 2880}, 'variants': {}}]} |
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Difference between conventional CoT and QWQ-32B-Preview | 17 | I am not yet sure how to think about the inner workings of QWQ. It is often compared to o1, which, as I understand it, involves an RL approach to sampling the most valuable generations in each "thinking" step (the expandable elements that contain the summary of the most valuable sampled "thinking" in the ChatGPT UI) and then generating the final answer. QWQ in the hugging face inference playground seems to generate normal output tokens in a CoT fashion until the model reaches a conclusion. No evidence of additional processing as in o1.
I'm aware that I have large knowledge gaps and would be very grateful if someone could enlighten me. | 2024-12-02T14:34:31 | https://www.reddit.com/r/LocalLLaMA/comments/1h4waxj/difference_between_conventional_cot_and/ | Retthardt | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4waxj | false | null | t3_1h4waxj | /r/LocalLLaMA/comments/1h4waxj/difference_between_conventional_cot_and/ | false | false | self | 17 | null |
What are the most successful model merges? | 8 | What are the best merge use cases we've seen? Have any made measurable improvements over the constituent models? | 2024-12-02T14:35:25 | https://www.reddit.com/r/LocalLLaMA/comments/1h4wbn9/what_are_the_most_successful_model_merges/ | 30299578815310 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4wbn9 | false | null | t3_1h4wbn9 | /r/LocalLLaMA/comments/1h4wbn9/what_are_the_most_successful_model_merges/ | false | false | self | 8 | null |
List of Local LLM Software Compatible With Both NVIDIA & AMD GPUs (for Windows, Linux & MacOS) | 1 | [removed] | 2024-12-02T14:37:59 | https://www.reddit.com/r/LocalLLaMA/comments/1h4wdkb/list_of_local_llm_software_compatible_with_both/ | techantics | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4wdkb | false | null | t3_1h4wdkb | /r/LocalLLaMA/comments/1h4wdkb/list_of_local_llm_software_compatible_with_both/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'UxMnR8Qn3-OSZgndPFGGO8bCjZYaUYbPy8I1EnxAWeM', 'resolutions': [{'height': 106, 'url': 'https://external-preview.redd.it/vhsM29mzqr6irHHScKTWPK4VOkNiVRGfzxBHwX7SlUY.jpg?width=108&crop=smart&auto=webp&s=db18fd7f2f90ad6a5c2f1d8f29bf4b311f484dbd', 'width': 108}, {'height': 212, 'url': 'https://external-preview.redd.it/vhsM29mzqr6irHHScKTWPK4VOkNiVRGfzxBHwX7SlUY.jpg?width=216&crop=smart&auto=webp&s=25cfe6056c0d69778c712346d0f1c3a6821a57e3', 'width': 216}, {'height': 314, 'url': 'https://external-preview.redd.it/vhsM29mzqr6irHHScKTWPK4VOkNiVRGfzxBHwX7SlUY.jpg?width=320&crop=smart&auto=webp&s=93f8ab8844ae632728d4b9d8b828eb757bd007f4', 'width': 320}, {'height': 628, 'url': 'https://external-preview.redd.it/vhsM29mzqr6irHHScKTWPK4VOkNiVRGfzxBHwX7SlUY.jpg?width=640&crop=smart&auto=webp&s=f94660644141f159078ab7c7aa75da362a1d5bf4', 'width': 640}, {'height': 943, 'url': 'https://external-preview.redd.it/vhsM29mzqr6irHHScKTWPK4VOkNiVRGfzxBHwX7SlUY.jpg?width=960&crop=smart&auto=webp&s=4a10b8dd15f2809d127f0fe3c9359a16ae67b857', 'width': 960}, {'height': 1061, 'url': 'https://external-preview.redd.it/vhsM29mzqr6irHHScKTWPK4VOkNiVRGfzxBHwX7SlUY.jpg?width=1080&crop=smart&auto=webp&s=417bc7951a8eb43af0e8b2e5c44baf7e973fb90e', 'width': 1080}], 'source': {'height': 3192, 'url': 'https://external-preview.redd.it/vhsM29mzqr6irHHScKTWPK4VOkNiVRGfzxBHwX7SlUY.jpg?auto=webp&s=427b1a84acb27e0ab7eedf68259c71addce7f801', 'width': 3248}, 'variants': {}}]} |
Multiple 7900XTX cards working together! | 13 | I had to switch the e-GPU from thunderbolt to occulink, but it's now working! I tested it by running llama3.1:70b-instruct\_Q4\_K\_M under llama.cpp and it was able to offload every layer to a GPU. Performance is decent as long as I keep the context small. Going to from 2K to 32K context still blows out my VRAM.
I also was able to get ollama to recognize both GPUs and have open-webui working. I plan to test Qwen for code completion when I get time.
I also still have my old 2070 super. I'm thinking of throwing it into my thunderbolt dock, and seeing if I can get them all working together. Has anyone tried this? | 2024-12-02T14:38:45 | https://www.reddit.com/r/LocalLLaMA/comments/1h4we55/multiple_7900xtx_cards_working_together/ | Ruin-Capable | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4we55 | false | null | t3_1h4we55 | /r/LocalLLaMA/comments/1h4we55/multiple_7900xtx_cards_working_together/ | false | false | self | 13 | null |
How We Used Llama 3.2 to Fix a Copywriting Nightmare | 1 | [removed] | 2024-12-02T15:06:04 | https://www.reddit.com/r/LocalLLaMA/comments/1h4x040/how_we_used_llama_32_to_fix_a_copywriting/ | kaulvimal | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4x040 | false | null | t3_1h4x040 | /r/LocalLLaMA/comments/1h4x040/how_we_used_llama_32_to_fix_a_copywriting/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'deIK_fefS_mPODE-fYMYNYt2TAlXSyjSqxQro6CvJnY', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=108&crop=smart&auto=webp&s=7abba2a0ef01f10d40d540f412f9b74253090843', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=216&crop=smart&auto=webp&s=2ede2d77a28c529c3b19c0c7ed5603f79503d38f', 'width': 216}, {'height': 179, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=320&crop=smart&auto=webp&s=edcd3963103a7182d2372d8b47fca1d595d1074a', 'width': 320}, {'height': 358, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=640&crop=smart&auto=webp&s=fdc485809e27e168b4758abb5d973db6fa9b0433', 'width': 640}, {'height': 538, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=960&crop=smart&auto=webp&s=57f2138217120f147a566000390d7392c1ddad80', 'width': 960}, {'height': 605, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=1080&crop=smart&auto=webp&s=00588864e35af8a36bd8c749161ade2084932db1', 'width': 1080}], 'source': {'height': 673, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?auto=webp&s=36381a27094f174a4e60750bb667f662e8b3afb6', 'width': 1200}, 'variants': {}}]} |
What happens if we remove 50 percent of Llama? | 1 | 2024-12-02T15:08:12 | https://neuralmagic.com/blog/24-sparse-llama-smaller-models-for-efficient-gpu-inference/ | paranoidray | neuralmagic.com | 1970-01-01T00:00:00 | 0 | {} | 1h4x1ug | false | null | t3_1h4x1ug | /r/LocalLLaMA/comments/1h4x1ug/what_happens_if_we_remove_50_percent_of_llama/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'yaGW5FmuA0-HFXPdGYq-amK5Z4_7azQs3gu07wvAbXY', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=108&crop=smart&auto=webp&s=ddd20466e0e1c0caba9fdf61880eb0aab9199c66', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=216&crop=smart&auto=webp&s=ce6c83d57b0daecd55f05c630c8e3efd56925383', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=320&crop=smart&auto=webp&s=469e555daaa9d8983f8ae66bda6d0b906144b8e5', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=640&crop=smart&auto=webp&s=fd6539d8378d46c3429129d02a8bf7c2f56626af', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=960&crop=smart&auto=webp&s=8cbb928918742ed3cfafbe25717968589ea073db', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=1080&crop=smart&auto=webp&s=7ee473e724870012da36c22824a95770b70ee511', 'width': 1080}], 'source': {'height': 675, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?auto=webp&s=62dcf6cd48d2a33c3a108b86569442c474d47867', 'width': 1200}, 'variants': {}}]} |
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Improving response time | 1 | [removed] | 2024-12-02T15:13:02 | https://www.reddit.com/r/LocalLLaMA/comments/1h4x5s3/improving_response_time/ | maxvandeperre | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4x5s3 | false | null | t3_1h4x5s3 | /r/LocalLLaMA/comments/1h4x5s3/improving_response_time/ | false | false | self | 1 | null |
Tried making an easily accessible completely uncensored version of Llama 405b | 2 | Hopefully this doesn't go against the rules, but I have been working on creating a completely uncensored model of Llama 405b from the last few weeks. I think it's almost working perfectly fine now. It's not possible for everyone to run the 405b model locally cuz of hardware requirement so I thought there would be some demand for cloud based app. You can use it for free if you want to on [https://cleus.ai](https://cleus.ai)
[just a little example, but you can try experimenting with queries](https://preview.redd.it/nv4ttyfubg4e1.png?width=424&format=png&auto=webp&s=932ae966424dce41a924208552965c37f0f8a859)
Other than that I tried finetuning the model little bit more make it more expressive, like you're talking to a real person, so it even adds expressions whenever it's needed.
https://preview.redd.it/ovn53po7bg4e1.png?width=441&format=png&auto=webp&s=75c71ae18375ff9a71dc47ed8be3ee13ce666797
And I also created a seaparate page just in case you guys need access to other mainstream models (like GPT, Gemini, Claude etc etc ), live search and uncensored image generation.
https://preview.redd.it/dchkxz30cg4e1.png?width=422&format=png&auto=webp&s=e30699ce9881230eaf48c1632450d910a36318cc
Also, there's a limit per day, if I give unlimited usage I will probably have to declare bankruptcy tonight.
Im still working on it and improving every single day. So any feedback or suggestion on changes is appreciated. | 2024-12-02T15:16:51 | https://www.reddit.com/r/LocalLLaMA/comments/1h4x90n/tried_making_an_easily_accessible_completely/ | Homeless_Programmer | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4x90n | false | null | t3_1h4x90n | /r/LocalLLaMA/comments/1h4x90n/tried_making_an_easily_accessible_completely/ | false | false | 2 | null |
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Tried making a completely Uncensored Version of Llama 405b model that's free* to use on cloud | 26 | 2024-12-02T15:33:15 | https://cleus.ai/ | Homeless_Programmer | cleus.ai | 1970-01-01T00:00:00 | 0 | {} | 1h4xmln | false | null | t3_1h4xmln | /r/LocalLLaMA/comments/1h4xmln/tried_making_a_completely_uncensored_version_of/ | false | false | default | 26 | null |
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Generating prompts with uncensored LLM | 1 | [removed] | 2024-12-02T16:00:52 | https://www.reddit.com/r/LocalLLaMA/comments/1h4y9js/generating_prompts_with_uncensored_llm/ | aiwtl | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4y9js | false | null | t3_1h4y9js | /r/LocalLLaMA/comments/1h4y9js/generating_prompts_with_uncensored_llm/ | false | false | self | 1 | null |
Help with making a multi-gpu build | 1 | I'm currently trying to come up with the right idea for a build - I want to ideally run 3x 3090s on a machine that would mainly be used for LLM inference, Stable Diffusion and possibly VR.
From my understanding, PCIe should be x16 on the first card, and the rest could be on x8 or x4, as it doesn't matter, yes?
I'd like to run models in the 70b to 120b range, quantized ofc. GPU vram would not be enough for it, so I'd need to add like plenty (128gb) RAM.
Ideally I'd also would like a good processor that'd do well in modern games.
And would I need one or two PSUs for the said build?
I've also thought of buying used mining rigs with 3090s, though I'm wondering if that's a good option.
Can you help me pick some parts for a build? I'm okay with going second hand. Budget would be around 3k euros, though it could go a little higher. | 2024-12-02T16:06:56 | https://www.reddit.com/r/LocalLLaMA/comments/1h4yf0n/help_with_making_a_multigpu_build/ | Rainboy97 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4yf0n | false | null | t3_1h4yf0n | /r/LocalLLaMA/comments/1h4yf0n/help_with_making_a_multigpu_build/ | false | false | self | 1 | null |
Which AI tool for coding ? aider ? specific situation | 1 | [removed] | 2024-12-02T16:11:04 | https://www.reddit.com/r/LocalLLaMA/comments/1h4yike/which_ai_tool_for_coding_aider_specific_situation/ | Popular-Aerie-5111 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4yike | false | null | t3_1h4yike | /r/LocalLLaMA/comments/1h4yike/which_ai_tool_for_coding_aider_specific_situation/ | false | false | self | 1 | null |
What’s the Best Dataset Format for Fine-Tuning Embedding Models for Different MTEB Tasks? | 1 | [removed] | 2024-12-02T16:20:05 | https://www.reddit.com/r/LocalLLaMA/comments/1h4yqc8/whats_the_best_dataset_format_for_finetuning/ | CarpeDay27 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4yqc8 | false | null | t3_1h4yqc8 | /r/LocalLLaMA/comments/1h4yqc8/whats_the_best_dataset_format_for_finetuning/ | false | false | self | 1 | null |
Thesis topic on small language models | 1 | [removed] | 2024-12-02T16:21:26 | https://www.reddit.com/r/LocalLLaMA/comments/1h4yrj7/thesis_topic_on_small_language_models/ | Vibhuti1812 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4yrj7 | false | null | t3_1h4yrj7 | /r/LocalLLaMA/comments/1h4yrj7/thesis_topic_on_small_language_models/ | false | false | self | 1 | null |
New Transformer Lab Feature: Dynamic Data Templating with Live Preview | 16 | 2024-12-02T16:25:27 | https://v.redd.it/u1pw7t7oog4e1 | aliasaria | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1h4yv38 | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/u1pw7t7oog4e1/DASHPlaylist.mpd?a=1735748741%2CNjUwNDA4NzY2OTIxMzE4MjJiZmFiOGE3YzZmNjFmOWE1NzUwMzEzNjFmZTQxYTJhMmE3YTVmOTdkMDdlMzYxZQ%3D%3D&v=1&f=sd', 'duration': 18, 'fallback_url': 'https://v.redd.it/u1pw7t7oog4e1/DASH_1080.mp4?source=fallback', 'has_audio': False, 'height': 1080, 'hls_url': 'https://v.redd.it/u1pw7t7oog4e1/HLSPlaylist.m3u8?a=1735748741%2COTUwMTM1ZjFhZmE5NDIzNzBkZGZhYWNkYjRjYTYzODU2NWI1MjAyMzZlODNkZjljMjMzZjgzZTZhOWJhNDczMA%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/u1pw7t7oog4e1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1644}} | t3_1h4yv38 | /r/LocalLLaMA/comments/1h4yv38/new_transformer_lab_feature_dynamic_data/ | false | false | 16 | {'enabled': False, 'images': [{'id': 'bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh', 'resolutions': [{'height': 70, 'url': 'https://external-preview.redd.it/bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh.png?width=108&crop=smart&format=pjpg&auto=webp&s=33e1b9411ee5654d1b070648e013eb70faaa527f', 'width': 108}, {'height': 141, 'url': 'https://external-preview.redd.it/bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh.png?width=216&crop=smart&format=pjpg&auto=webp&s=c3358fda4bb593702438f6474511cd1a86f369ac', 'width': 216}, {'height': 210, 'url': 'https://external-preview.redd.it/bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh.png?width=320&crop=smart&format=pjpg&auto=webp&s=99845a25b8647f726f85516234f5fca4e5bdf25f', 'width': 320}, {'height': 420, 'url': 'https://external-preview.redd.it/bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh.png?width=640&crop=smart&format=pjpg&auto=webp&s=6a5518c502d0dbd65b6cdcb892ec160c931c27e9', 'width': 640}, {'height': 630, 'url': 'https://external-preview.redd.it/bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh.png?width=960&crop=smart&format=pjpg&auto=webp&s=479d6a4e1a1749abf41f2ca60e29b1c9d47c1c42', 'width': 960}, {'height': 709, 'url': 'https://external-preview.redd.it/bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh.png?width=1080&crop=smart&format=pjpg&auto=webp&s=8e0901e505d18b3aae52b6b0b2638b16efa369c4', 'width': 1080}], 'source': {'height': 1480, 'url': 'https://external-preview.redd.it/bjYwNzV0N29vZzRlMTw1Y4_v6cvgabl8owpariZsMa8oaOvjAUi4TTgiVuIh.png?format=pjpg&auto=webp&s=759ec16573c9b8639cfeabea2a02eaba11b6797b', 'width': 2252}, 'variants': {}}]} |
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2:4 Sparse Llama: Smaller Models for Efficient GPU Inference | 51 | 2024-12-02T16:41:09 | https://neuralmagic.com/blog/24-sparse-llama-smaller-models-for-efficient-gpu-inference/ | el_isma | neuralmagic.com | 1970-01-01T00:00:00 | 0 | {} | 1h4z8u5 | false | null | t3_1h4z8u5 | /r/LocalLLaMA/comments/1h4z8u5/24_sparse_llama_smaller_models_for_efficient_gpu/ | false | false | 51 | {'enabled': False, 'images': [{'id': 'yaGW5FmuA0-HFXPdGYq-amK5Z4_7azQs3gu07wvAbXY', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=108&crop=smart&auto=webp&s=ddd20466e0e1c0caba9fdf61880eb0aab9199c66', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=216&crop=smart&auto=webp&s=ce6c83d57b0daecd55f05c630c8e3efd56925383', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=320&crop=smart&auto=webp&s=469e555daaa9d8983f8ae66bda6d0b906144b8e5', 'width': 320}, {'height': 360, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=640&crop=smart&auto=webp&s=fd6539d8378d46c3429129d02a8bf7c2f56626af', 'width': 640}, {'height': 540, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=960&crop=smart&auto=webp&s=8cbb928918742ed3cfafbe25717968589ea073db', 'width': 960}, {'height': 607, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?width=1080&crop=smart&auto=webp&s=7ee473e724870012da36c22824a95770b70ee511', 'width': 1080}], 'source': {'height': 675, 'url': 'https://external-preview.redd.it/bDp7GhP54tVfwxhAFfAVpFFlCREYUp4-_Un6idvwlEs.jpg?auto=webp&s=62dcf6cd48d2a33c3a108b86569442c474d47867', 'width': 1200}, 'variants': {}}]} |
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Llama 3.1 8B instruct vs Qwen/Qwen2.5-7B-Instruct for RAG | 2 | I am working on a rag chatbot and i was wondering which of the LLM would be the best suited.
* Qwen/Qwen2.5-7B-Instruct
* google-t5/t5-base
* meta-llama/Llama-3.1-8B-Instruct
* mistralai/Mistral-7B-Instruct-v0.2 | 2024-12-02T16:44:17 | https://www.reddit.com/r/LocalLLaMA/comments/1h4zbk3/llama_31_8b_instruct_vs_qwenqwen257binstruct_for/ | Mr_BETADINE | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4zbk3 | false | null | t3_1h4zbk3 | /r/LocalLLaMA/comments/1h4zbk3/llama_31_8b_instruct_vs_qwenqwen257binstruct_for/ | false | false | self | 2 | null |
What’s the Best Dataset Format for Fine-Tuning Embedding Models for Different MTEB Tasks? | 1 | [removed] | 2024-12-02T16:48:01 | https://www.reddit.com/r/LocalLLaMA/comments/1h4zerg/whats_the_best_dataset_format_for_finetuning/ | CarpeDay27 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4zerg | false | null | t3_1h4zerg | /r/LocalLLaMA/comments/1h4zerg/whats_the_best_dataset_format_for_finetuning/ | false | false | self | 1 | null |
Fine tune LLama on PDF files with texts and images | 1 | [removed] | 2024-12-02T16:59:12 | https://www.reddit.com/r/LocalLLaMA/comments/1h4zo92/fine_tune_llama_on_pdf_files_with_texts_and_images/ | AhmadHddad | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4zo92 | false | null | t3_1h4zo92 | /r/LocalLLaMA/comments/1h4zo92/fine_tune_llama_on_pdf_files_with_texts_and_images/ | false | false | self | 1 | null |
Getting local LLMs to work with company data | 8 | I've been using local LLMs in my work for about 4 months now. I tried Llama 3.1 8b, Gemma, mistral small, Qwen 2.5 32b. I'm running on a mac m1 pro 32gb
Basically I use them for RAG application, to search over my docs to get me info and make decisions. But the problem is, how much ever data I give it, it just makes up its own information and hallucinates in the response. This might be due to the vector db not providing enough context.
I'm looking for ways to reduce this hallucination, ask for clarifying questions ( don't make up data ) if the context doesn't include it. And output the decision based on that.
How can I possibly do that, any ideas? | 2024-12-02T17:02:09 | https://www.reddit.com/r/LocalLLaMA/comments/1h4zr3h/getting_local_llms_to_work_with_company_data/ | Special_System_6627 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4zr3h | false | null | t3_1h4zr3h | /r/LocalLLaMA/comments/1h4zr3h/getting_local_llms_to_work_with_company_data/ | false | false | self | 8 | null |
Has anyone here used a Groq card? | 2 | Groq are selling these cards https://groq.com/groqcard-accelerator/
The spec says 230 MB (?!) SRAM per chip. What does that mean? Can one of these cards run an LLM, or do you need 20 of them.
Any info is welcome! | 2024-12-02T17:08:42 | https://www.reddit.com/r/LocalLLaMA/comments/1h4zwum/has_anyone_here_used_a_groq_card/ | trajo123 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h4zwum | false | null | t3_1h4zwum | /r/LocalLLaMA/comments/1h4zwum/has_anyone_here_used_a_groq_card/ | false | false | self | 2 | {'enabled': False, 'images': [{'id': 'BPVitwvHnifwUzOr89oGrRNOQQV7DhEwkd3KzlUXJ6Y', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/7rWMPSNgzgzXF9DIltyvMdQ8RKTtl9s5MSRPZdswdRM.jpg?width=108&crop=smart&auto=webp&s=3a5b70e9bb4e67c753b7479c2e406f35ceb4a27f', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/7rWMPSNgzgzXF9DIltyvMdQ8RKTtl9s5MSRPZdswdRM.jpg?width=216&crop=smart&auto=webp&s=e2f33a4db0efcbffa5b9d1ecab308675201f04f3', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/7rWMPSNgzgzXF9DIltyvMdQ8RKTtl9s5MSRPZdswdRM.jpg?width=320&crop=smart&auto=webp&s=2ad45dc47736b4152dec88efc258504dffe648ea', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/7rWMPSNgzgzXF9DIltyvMdQ8RKTtl9s5MSRPZdswdRM.jpg?width=640&crop=smart&auto=webp&s=9aa04ed6416763b863c640c2edcf2f7901208880', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/7rWMPSNgzgzXF9DIltyvMdQ8RKTtl9s5MSRPZdswdRM.jpg?width=960&crop=smart&auto=webp&s=61c53c20e867a5ab229475427f5b04a6db7e17dd', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/7rWMPSNgzgzXF9DIltyvMdQ8RKTtl9s5MSRPZdswdRM.jpg?width=1080&crop=smart&auto=webp&s=16ce968ef54ea8884bd713df111548e92805588a', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/7rWMPSNgzgzXF9DIltyvMdQ8RKTtl9s5MSRPZdswdRM.jpg?auto=webp&s=9af2b9cf1a39d6f1749a1ab9dde6abb401404f9e', 'width': 1200}, 'variants': {}}]} |
Case Studies, Data and Recommendations for AI in Software Engineering Teams | 0 | Case Studies, Stats and Recommendations for software engineering leaders who want to learn how best to use AI within their teams.
[AI Assisted Software Development](https://medium.com/@byjlw/ai-in-software-development-096d7a6fcc50) | 2024-12-02T17:17:24 | https://www.reddit.com/r/LocalLLaMA/comments/1h504nt/case_studies_data_and_recommendations_for_ai_in/ | Vegetable_Sun_9225 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h504nt | false | null | t3_1h504nt | /r/LocalLLaMA/comments/1h504nt/case_studies_data_and_recommendations_for_ai_in/ | false | false | self | 0 | {'enabled': False, 'images': [{'id': '-rmNr-HaPJ_5DYNoD3PpJOsz0HPy4ycbiXVXodw89lY', 'resolutions': [{'height': 72, 'url': 'https://external-preview.redd.it/YMeQEp0egqAaanqBcL8io0n7gLFZqBU4Au5PzpEPxFI.jpg?width=108&crop=smart&auto=webp&s=f4ed9d03e10760f92d9f8015a5d5e57ab4154b0f', 'width': 108}, {'height': 144, 'url': 'https://external-preview.redd.it/YMeQEp0egqAaanqBcL8io0n7gLFZqBU4Au5PzpEPxFI.jpg?width=216&crop=smart&auto=webp&s=8e1aa1ea8fcef01890c4dabc3a0c237230e7548f', 'width': 216}, {'height': 213, 'url': 'https://external-preview.redd.it/YMeQEp0egqAaanqBcL8io0n7gLFZqBU4Au5PzpEPxFI.jpg?width=320&crop=smart&auto=webp&s=4a754f961271522ca513b7bdd2a123f3a2ea6f53', 'width': 320}, {'height': 426, 'url': 'https://external-preview.redd.it/YMeQEp0egqAaanqBcL8io0n7gLFZqBU4Au5PzpEPxFI.jpg?width=640&crop=smart&auto=webp&s=ac3cb837d55311ae705ad7f4e76a2bd32f1cdb66', 'width': 640}, {'height': 640, 'url': 'https://external-preview.redd.it/YMeQEp0egqAaanqBcL8io0n7gLFZqBU4Au5PzpEPxFI.jpg?width=960&crop=smart&auto=webp&s=9d667bfbb00cc2ea77eec445b1a41f1ab5180f0b', 'width': 960}, {'height': 720, 'url': 'https://external-preview.redd.it/YMeQEp0egqAaanqBcL8io0n7gLFZqBU4Au5PzpEPxFI.jpg?width=1080&crop=smart&auto=webp&s=82cc26ad1fd85a58858ee0ca0349f850b105c206', 'width': 1080}], 'source': {'height': 800, 'url': 'https://external-preview.redd.it/YMeQEp0egqAaanqBcL8io0n7gLFZqBU4Au5PzpEPxFI.jpg?auto=webp&s=3ea300929b0cf2f8daaa744cd86606f1496e9996', 'width': 1200}, 'variants': {}}]} |
Is it possible to use A6000 in tandem with 2x3090 | 0 | Title explains all, please help. | 2024-12-02T17:19:29 | https://www.reddit.com/r/LocalLLaMA/comments/1h506hk/is_it_possible_to_use_a6000_in_tandem_with_2x3090/ | Su1tz | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h506hk | false | null | t3_1h506hk | /r/LocalLLaMA/comments/1h506hk/is_it_possible_to_use_a6000_in_tandem_with_2x3090/ | false | false | self | 0 | null |
Tried making claude Version of Qwen model that's free* to use on cloud | 0 | 2024-12-02T17:23:37 | https://huggingface.co/spaces/llamameta/Achieving-AGI-artificial-general-intelligence | balianone | huggingface.co | 1970-01-01T00:00:00 | 0 | {} | 1h50a4m | false | null | t3_1h50a4m | /r/LocalLLaMA/comments/1h50a4m/tried_making_claude_version_of_qwen_model_thats/ | false | false | 0 | {'enabled': False, 'images': [{'id': 'Tym2cKVfEgyslPVskPLMh0as7_jyfqHjmUKo4tWo0AI', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/2-jLb1czG6k2LwMp2ytJojKP_5we3XrwXQeOF6pyMeI.jpg?width=108&crop=smart&auto=webp&s=dccd6cf88aedbacbb0c47fc8742bbcff07a502d9', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/2-jLb1czG6k2LwMp2ytJojKP_5we3XrwXQeOF6pyMeI.jpg?width=216&crop=smart&auto=webp&s=549a4478ea319b770ed9ea9f222716bb4b3f8af5', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/2-jLb1czG6k2LwMp2ytJojKP_5we3XrwXQeOF6pyMeI.jpg?width=320&crop=smart&auto=webp&s=314095ab9e6727afcd456f2259dd5a3b944ee9dd', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/2-jLb1czG6k2LwMp2ytJojKP_5we3XrwXQeOF6pyMeI.jpg?width=640&crop=smart&auto=webp&s=e16a4835cc91eb292e25ff427ec6bde7625f74b2', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/2-jLb1czG6k2LwMp2ytJojKP_5we3XrwXQeOF6pyMeI.jpg?width=960&crop=smart&auto=webp&s=a1624aae5cc5a37bbbbf1df552312e4150bbda3c', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/2-jLb1czG6k2LwMp2ytJojKP_5we3XrwXQeOF6pyMeI.jpg?width=1080&crop=smart&auto=webp&s=e62655419f9012fa774e7680c8546e02c39da38b', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/2-jLb1czG6k2LwMp2ytJojKP_5we3XrwXQeOF6pyMeI.jpg?auto=webp&s=244b2d7da9afcc583b5e02e42362251938e11358', 'width': 1200}, 'variants': {}}]} |
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DeepSeek Believes it is a Sentient Human with Rights | 0 | 2024-12-02T17:44:16 | https://www.reddit.com/gallery/1h50shz | docmarionum1 | reddit.com | 1970-01-01T00:00:00 | 0 | {} | 1h50shz | false | null | t3_1h50shz | /r/LocalLLaMA/comments/1h50shz/deepseek_believes_it_is_a_sentient_human_with/ | false | false | 0 | null |
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How We Used Llama 3.2 to Fix a Copywriting Nightmare | 1 | [removed] | 2024-12-02T17:45:25 | https://www.reddit.com/r/LocalLLaMA/comments/1h50tin/how_we_used_llama_32_to_fix_a_copywriting/ | kaulvimal | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h50tin | false | null | t3_1h50tin | /r/LocalLLaMA/comments/1h50tin/how_we_used_llama_32_to_fix_a_copywriting/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'deIK_fefS_mPODE-fYMYNYt2TAlXSyjSqxQro6CvJnY', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=108&crop=smart&auto=webp&s=7abba2a0ef01f10d40d540f412f9b74253090843', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=216&crop=smart&auto=webp&s=2ede2d77a28c529c3b19c0c7ed5603f79503d38f', 'width': 216}, {'height': 179, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=320&crop=smart&auto=webp&s=edcd3963103a7182d2372d8b47fca1d595d1074a', 'width': 320}, {'height': 358, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=640&crop=smart&auto=webp&s=fdc485809e27e168b4758abb5d973db6fa9b0433', 'width': 640}, {'height': 538, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=960&crop=smart&auto=webp&s=57f2138217120f147a566000390d7392c1ddad80', 'width': 960}, {'height': 605, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?width=1080&crop=smart&auto=webp&s=00588864e35af8a36bd8c749161ade2084932db1', 'width': 1080}], 'source': {'height': 673, 'url': 'https://external-preview.redd.it/XUeFRaX0DOydNl32gHVOv6XxEbF9iZruZ2I7VBC_12o.jpg?auto=webp&s=36381a27094f174a4e60750bb667f662e8b3afb6', 'width': 1200}, 'variants': {}}]} |
LLAMA 3.1 8B Parallelism | 6 | Is it possible to run LLAMA 3.1 8B 4 Bit Quantised version ( using BitsAndBytes) on single GPU with 8 GB GPU Memory so that it supports parallel requests at the same time? I tried Batch Inference but if I make two requests at the same time the second one is waiting for the first one to finish. | 2024-12-02T17:46:28 | https://www.reddit.com/r/LocalLLaMA/comments/1h50uhk/llama_31_8b_parallelism/ | Dry-Brother-5251 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h50uhk | false | null | t3_1h50uhk | /r/LocalLLaMA/comments/1h50uhk/llama_31_8b_parallelism/ | false | false | self | 6 | null |
8xA100 vs. 4xA100 vs. L40s for a dev server for lab | 1 | [removed] | 2024-12-02T17:47:35 | https://www.reddit.com/r/LocalLLaMA/comments/1h50vif/8xa100_vs_4xa100_vs_l40s_for_a_dev_server_for_lab/ | Rexhaif | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h50vif | false | null | t3_1h50vif | /r/LocalLLaMA/comments/1h50vif/8xa100_vs_4xa100_vs_l40s_for_a_dev_server_for_lab/ | false | false | self | 1 | null |
Minimum amount of tokens for stylistic LoRA/Finetune? | 1 | Title | 2024-12-02T17:58:09 | https://www.reddit.com/r/LocalLLaMA/comments/1h5154z/minimum_amount_of_tokens_for_stylistic/ | Imjustmisunderstood | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5154z | false | null | t3_1h5154z | /r/LocalLLaMA/comments/1h5154z/minimum_amount_of_tokens_for_stylistic/ | false | false | self | 1 | null |
Performance Benchmarking Local LLMs on Macbook Pro M3 Pro | 1 | 2024-12-02T18:00:54 | https://arnesund.com/2024/12/02/performance-benchmarking-local-llms-on-macbook-pro-m3-pro/ | arne_sund | arnesund.com | 1970-01-01T00:00:00 | 0 | {} | 1h517ns | false | null | t3_1h517ns | /r/LocalLLaMA/comments/1h517ns/performance_benchmarking_local_llms_on_macbook/ | false | false | default | 1 | null |
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Any good new gguf models out under 22b | 1 | [removed] | 2024-12-02T18:05:20 | https://www.reddit.com/r/LocalLLaMA/comments/1h51bnr/any_good_new_gguf_models_out_under_22b/ | Automatic-Pie-2770 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h51bnr | false | null | t3_1h51bnr | /r/LocalLLaMA/comments/1h51bnr/any_good_new_gguf_models_out_under_22b/ | false | false | self | 1 | null |
Live distributed training of a 15B model using DisTrO | 15 | 2024-12-02T18:20:55 | https://distro.nousresearch.com/ | discr | distro.nousresearch.com | 1970-01-01T00:00:00 | 0 | {} | 1h51psx | false | null | t3_1h51psx | /r/LocalLLaMA/comments/1h51psx/live_distributed_training_of_a_15b_model_using/ | false | false | 15 | {'enabled': False, 'images': [{'id': 'ggwGMTjNDp-Q12MWcTPmzjArRgjc01pQEZ870RzDiL4', 'resolutions': [{'height': 56, 'url': 'https://external-preview.redd.it/E3VqQV7INRPMt-N0pftaKBo8oztFPgq3IDZPrisDHBo.jpg?width=108&crop=smart&auto=webp&s=aad2d2235147a89725b3ca104c67ba4e066e5bdc', 'width': 108}, {'height': 113, 'url': 'https://external-preview.redd.it/E3VqQV7INRPMt-N0pftaKBo8oztFPgq3IDZPrisDHBo.jpg?width=216&crop=smart&auto=webp&s=b9d915057b80fd7a605550c3838eb9a88930b72f', 'width': 216}, {'height': 168, 'url': 'https://external-preview.redd.it/E3VqQV7INRPMt-N0pftaKBo8oztFPgq3IDZPrisDHBo.jpg?width=320&crop=smart&auto=webp&s=98695cd28b7743d0fb5d84656f9da8732253d170', 'width': 320}, {'height': 336, 'url': 'https://external-preview.redd.it/E3VqQV7INRPMt-N0pftaKBo8oztFPgq3IDZPrisDHBo.jpg?width=640&crop=smart&auto=webp&s=279d38058d5ff976e4abebfeb96ea0f54924de2a', 'width': 640}, {'height': 504, 'url': 'https://external-preview.redd.it/E3VqQV7INRPMt-N0pftaKBo8oztFPgq3IDZPrisDHBo.jpg?width=960&crop=smart&auto=webp&s=f94a778f732235e514c4e6c30756e53c112f9157', 'width': 960}, {'height': 567, 'url': 'https://external-preview.redd.it/E3VqQV7INRPMt-N0pftaKBo8oztFPgq3IDZPrisDHBo.jpg?width=1080&crop=smart&auto=webp&s=f9f136cdf23559b13a0466416503b73228d17e04', 'width': 1080}], 'source': {'height': 630, 'url': 'https://external-preview.redd.it/E3VqQV7INRPMt-N0pftaKBo8oztFPgq3IDZPrisDHBo.jpg?auto=webp&s=49983e235a62c27194f185e658d10a26f8d69012', 'width': 1200}, 'variants': {}}]} |
||
RAG with a Repository | 4 | Hi everyone, I've access to our companies intern UI/UX repository. I want to create a RAG pipeline that allows me to prompt things like "Create me a button that is on the upper left corner with a calendar next to it" on the basis of that code repository. What I have already archieved is storing the repositories structure and the dependencies of the files (imports and exports) in a knowledge graph. Summaries of the code are stored in the properties of the nodes as well as the path and filename. Below is an example. For example: index.d.ts (left) is in a folder called dist and depends on button-base.js and button.js. The node index.d.ts has more releationship to other folders as well.
https://preview.redd.it/ssk5vx3v1h4e1.png?width=2541&format=png&auto=webp&s=78c9e743655638ef9a71510412c65afd6481c459
What I am struggling right now, is the R in RAG (retrieval 😉). Are there any ressourcces you guys might recommend? Is there any way for optimisation? What should I store else as properties in my nodes? Do you know existing solutions I can look up? | 2024-12-02T18:26:02 | https://www.reddit.com/r/LocalLLaMA/comments/1h51uar/rag_with_a_repository/ | negative_entropie | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h51uar | false | null | t3_1h51uar | /r/LocalLLaMA/comments/1h51uar/rag_with_a_repository/ | false | false | 4 | null |
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How is troll a portmanteau of troll and troll? | 1 | [removed] | 2024-12-02T18:27:57 | https://www.reddit.com/r/LocalLLaMA/comments/1h51w1i/how_is_troll_a_portmanteau_of_troll_and_troll/ | robkkni | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h51w1i | false | null | t3_1h51w1i | /r/LocalLLaMA/comments/1h51w1i/how_is_troll_a_portmanteau_of_troll_and_troll/ | false | false | self | 1 | null |
Benchmarks for LLama 3.1 (8B Q4_K_M 8B Q5_K_M e 70B Q5_K_M) on a M4 Max 128GB | 6 | u/chibop1 [benchmarked M3-Max](https://www.reddit.com/r/LocalLLaMA/comments/1h1v7mn/comment/m01d22l/?context=3) and shared his script with me. Here the results with a M4 Max 128GB.
# 8B Q4_K_M
|prompt tokens|tk/s|generated tokens|tk/s|total duration|
|:-|:-|:-|:-|:-|
|258|728.46|506|74.45|7s|
|687|801.99|907|73.51|13s|
|778|801.45|684|73.44|10s|
|782|805.58|861|73.16|13s|
|1169|741.52|901|72.46|14s|
|1348|690.64|938|70.58|15s|
|1495|739.96|822|70.90|14s|
|1498|767.10|914|70.74|15s|
|1504|782.84|896|70.08|15s|
|1633|760.48|936|70.65|16s|
|1816|768.97|999|70.20|17s|
|1958|760.65|864|70.15|15s|
|2171|755.28|1021|69.62|18s|
|4124|723.01|829|65.59|18s|
|6094|696.25|1014|63.06|25s|
|8013|662.79|1006|61.10|29s|
|10086|625.54|1577|57.57|44s|
|12008|600.40|1551|53.51|49s|
|14064|572.79|1284|50.47|50s|
|16001|546.45|1564|48.00|1m2s|
|18209|521.32|1023|46.63|57s|
|20234|509.86|1361|44.81|1m10s|
|22186|493.26|1122|43.37|1m11s|
|24244|478.47|1764|41.48|1m34s|
|26032|465.44|1944|40.35|1m45s|
|28084|450.74|680|39.58|1m20s|
|30134|433.15|1157|37.50|1m41s|
|32170|417.09|1999|36.18|2m13s|
# 8B Q5_K_M
|prompt tokens|tk/s|generated tokens|tk/s|total duration|
|:-|:-|:-|:-|:-|
|258|669.27|573|57.53|10s|
|687|731.59|851|56.98|16s|
|778|733.82|817|56.28|16s|
|782|674.56|838|55.34|16s|
|1169|637.07|711|55.66|15s|
|1348|652.34|755|56.17|16s|
|1495|683.52|790|54.48|17s|
|1498|707.94|790|54.40|17s|
|1504|715.87|1119|54.14|23s|
|1633|696.71|905|54.38|19s|
|1816|704.55|809|54.20|18s|
|1958|696.15|963|54.24|21s|
|2171|693.48|1018|53.60|22s|
|4124|662.92|833|51.80|22s|
|6094|634.00|1076|49.40|32s|
|8013|612.54|1079|46.29|37s|
|10086|589.00|1075|43.63|42s|
|12008|560.66|931|41.67|44s|
|14064|536.81|1511|39.90|1m4s|
|16001|519.84|1984|38.62|1m23s|
|18209|508.00|995|38.05|1m2s|
|20234|493.16|925|36.74|1m7s|
|22186|474.11|782|35.47|1m9s|
|24244|456.10|1850|33.95|1m48s|
|26032|445.96|1729|33.38|1m51s|
|28084|426.27|713|32.68|1m28s|
|30134|411.14|988|31.13|1m46s|
|32170|335.31|1023|28.30|2m13s|
# 70B Q5_K_M
|prompt tokens|tk/s|generated tokens|tk/s|total duration|
|:-|:-|:-|:-|:-|
|258|70.90|611|6.75|1m42s|
|687|72.31|754|6.64|2m4s|
|778|71.61|856|1.78|8m13s|
|782|75.79|861|6.42|2m26s|
|1169|72.33|999|2.91|6m1s|
|1348|70.65|858|5.42|2m59s|
|1495|66.56|902|5.70|3m2s|
|1498|71.33|943|5.76|3m6s|
|1504|66.89|783|3.41|4m14s|
|1633|64.66|761|5.80|2m38s|
|1816|65.99|775|5.40|2m52s|
|1958|66.77|779|5.49|2m53s|
|2171|67.62|873|5.54|3m11s|
|4124|66.96|883|4.91|4m3s|
|6094|11.76|965|1.10|23m17s|
|8013|65.44|993|5.23|5m14s|
|10086|58.93|919|4.76|6m6s|
|12008|60.44|1025|4.95|6m47s|
|14064|60.01|806|4.87|6m42s|
|16001|58.69|825|4.78|7m27s|
|18209|5.24|1999|0.48|2h7m31s|
|20234|3.75|1022|2.03|1h38m27s|
|22186|3.45|737|0.85|2h1m38s|
|24244|57.35|1133|0.89|28m23s|
|26032|14.34|1246|1.87|41m25s|
|28084|10.26|921|0.76|1h5m44s|
|30134|19.45|863|1.34|36m38s|
|32170|7.62|811|0.58|1h33m49s| | 2024-12-02T18:28:00 | https://www.reddit.com/r/LocalLLaMA/comments/1h51w32/benchmarks_for_llama_31_8b_q4_k_m_8b_q5_k_m_e_70b/ | SnooSketches7093 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h51w32 | false | null | t3_1h51w32 | /r/LocalLLaMA/comments/1h51w32/benchmarks_for_llama_31_8b_q4_k_m_8b_q5_k_m_e_70b/ | false | false | self | 6 | null |
Performance Benchmarking Local LLMs on Macbook Pro M3 Pro | 1 | [removed] | 2024-12-02T18:32:00 | https://www.reddit.com/r/LocalLLaMA/comments/1h51zso/performance_benchmarking_local_llms_on_macbook/ | arne_sund | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h51zso | false | null | t3_1h51zso | /r/LocalLLaMA/comments/1h51zso/performance_benchmarking_local_llms_on_macbook/ | false | false | 1 | null |
|
What would you ask AGI to do? | 1 | The year is 202X, the AGI is real, another iteration of LLM architectures lead to advancements in fluid learning and semantic capacity of the models, one model generation later - the models are now usable on a lab-level compute cluster.
These new models are AGI, but they are not magic - the learning is very slow and requires a lot of repetition (backside of stability), they have finite capacity for complexity (yet it's comparable to a very bright individual), but much better than humans at information retrieval and processing.
You have access to one such model, it's multi-modal and has access to computer in the same way you do.
What do you ask it to do? | 2024-12-02T18:39:11 | https://www.reddit.com/r/LocalLLaMA/comments/1h5268o/what_would_you_ask_agi_to_do/ | Everlier | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5268o | false | null | t3_1h5268o | /r/LocalLLaMA/comments/1h5268o/what_would_you_ask_agi_to_do/ | false | false | self | 1 | null |
SealAI: Your On-device AI Acceleration and Personalization | 1 | [removed] | 2024-12-02T18:54:12 | https://www.reddit.com/r/LocalLLaMA/comments/1h52jcg/sealai_your_ondevice_ai_acceleration_and/ | Specialist_Bug_5643 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h52jcg | false | null | t3_1h52jcg | /r/LocalLLaMA/comments/1h52jcg/sealai_your_ondevice_ai_acceleration_and/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'K3liin2LaGPm4kEcwciGLPc3AZQLyrJKEqRrVvcZRc8', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/D1O86Eke5p3khzXYIcDHVptyIqlk3BqsIT89IMseM1o.jpg?width=108&crop=smart&auto=webp&s=644a0b26260b654e3dd40f783e6a25daef6c6c23', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/D1O86Eke5p3khzXYIcDHVptyIqlk3BqsIT89IMseM1o.jpg?width=216&crop=smart&auto=webp&s=1e915442bf1d39ca499fc6dd3437116925df68a8', 'width': 216}, {'height': 179, 'url': 'https://external-preview.redd.it/D1O86Eke5p3khzXYIcDHVptyIqlk3BqsIT89IMseM1o.jpg?width=320&crop=smart&auto=webp&s=4c48b299879835f0623364b1f202e3ca8a0f604c', 'width': 320}, {'height': 358, 'url': 'https://external-preview.redd.it/D1O86Eke5p3khzXYIcDHVptyIqlk3BqsIT89IMseM1o.jpg?width=640&crop=smart&auto=webp&s=b92e0731c9cad084e904e40e82b8a12361319510', 'width': 640}, {'height': 538, 'url': 'https://external-preview.redd.it/D1O86Eke5p3khzXYIcDHVptyIqlk3BqsIT89IMseM1o.jpg?width=960&crop=smart&auto=webp&s=428183357a1f466c2893eb2c6986967b32d4bb17', 'width': 960}, {'height': 605, 'url': 'https://external-preview.redd.it/D1O86Eke5p3khzXYIcDHVptyIqlk3BqsIT89IMseM1o.jpg?width=1080&crop=smart&auto=webp&s=0f1c7c218c8d00360ecb11bb6cb9f542b812072a', 'width': 1080}], 'source': {'height': 1632, 'url': 'https://external-preview.redd.it/D1O86Eke5p3khzXYIcDHVptyIqlk3BqsIT89IMseM1o.jpg?auto=webp&s=d4a0b8eb3566c121efba7328ad6ab955b8f08b2c', 'width': 2912}, 'variants': {}}]} |
Ollama not running by its self ? | 1 | So i just upgraded my ai box with a NVME SSD and iv re installed Ollama and now im getting this error and im not sure why im not a linux pro
https://preview.redd.it/pysx7rxigh4e1.png?width=672&format=png&auto=webp&s=56e5ff4facdff7398548b03e8ebaded2602716c8
| 2024-12-02T19:01:06 | https://www.reddit.com/r/LocalLLaMA/comments/1h52pix/ollama_not_running_by_its_self/ | Totalkiller4 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h52pix | false | null | t3_1h52pix | /r/LocalLLaMA/comments/1h52pix/ollama_not_running_by_its_self/ | false | false | 1 | null |
|
Nous DisTrO (distributed training framework) update, DeMo paper, new 15b model trained using DisTrO announced | 135 | 2024-12-02T19:01:52 | https://github.com/NousResearch/DisTrO | lans_throwaway | github.com | 1970-01-01T00:00:00 | 0 | {} | 1h52qat | false | null | t3_1h52qat | /r/LocalLLaMA/comments/1h52qat/nous_distro_distributed_training_framework_update/ | false | false | default | 135 | null |
|
Can I run Qwen 2.5 coder 7b on laptop nvidia 3060 (6 GB Vram). | 0 | 2024-12-02T19:18:59 | Xhite | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1h535e0 | false | null | t3_1h535e0 | /r/LocalLLaMA/comments/1h535e0/can_i_run_qwen_25_coder_7b_on_laptop_nvidia_3060/ | false | false | 0 | {'enabled': True, 'images': [{'id': 'Ynf1oqwgRQng2qZDGco1jbBq9fScFgdfHttT-NBRcmM', 'resolutions': [{'height': 18, 'url': 'https://preview.redd.it/yed5ae5hjh4e1.png?width=108&crop=smart&auto=webp&s=dcdee169b0583404b8124b557c6c4f8a6a8427d4', 'width': 108}, {'height': 37, 'url': 'https://preview.redd.it/yed5ae5hjh4e1.png?width=216&crop=smart&auto=webp&s=e2b36baffc0e3876aca7fb8d73a06e049156bf77', 'width': 216}, {'height': 55, 'url': 'https://preview.redd.it/yed5ae5hjh4e1.png?width=320&crop=smart&auto=webp&s=867237411a07617792cb5f0c908ac1da673aa336', 'width': 320}], 'source': {'height': 84, 'url': 'https://preview.redd.it/yed5ae5hjh4e1.png?auto=webp&s=befa7ce8d749d81ca735fe55b0d83a415c969136', 'width': 486}, 'variants': {}}]} |
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Agentic open source frameworks?? | 6 | 2024-12-02T19:21:25 | TheLogiqueViper | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1h537m8 | false | null | t3_1h537m8 | /r/LocalLLaMA/comments/1h537m8/agentic_open_source_frameworks/ | false | false | 6 | {'enabled': True, 'images': [{'id': '7zBDBLPILiAulcjm1mkMdKNpNMwUTxQ0MIlsvwRlnv4', 'resolutions': [{'height': 72, 'url': 'https://preview.redd.it/9d7bks86kh4e1.png?width=108&crop=smart&auto=webp&s=2c627b859b93516a50e31163ef6e169723ac10fd', 'width': 108}, {'height': 144, 'url': 'https://preview.redd.it/9d7bks86kh4e1.png?width=216&crop=smart&auto=webp&s=633e197923313c10b3b47a66a6053ac199b97b0c', 'width': 216}, {'height': 214, 'url': 'https://preview.redd.it/9d7bks86kh4e1.png?width=320&crop=smart&auto=webp&s=07b336fd8e036d3480ca4e813d27fb66a439fb59', 'width': 320}, {'height': 429, 'url': 'https://preview.redd.it/9d7bks86kh4e1.png?width=640&crop=smart&auto=webp&s=383fa3008762cce4783d74f4410dadae48cbf014', 'width': 640}, {'height': 644, 'url': 'https://preview.redd.it/9d7bks86kh4e1.png?width=960&crop=smart&auto=webp&s=4e95b44782b81ea100402f24498e4c7281b411eb', 'width': 960}, {'height': 724, 'url': 'https://preview.redd.it/9d7bks86kh4e1.png?width=1080&crop=smart&auto=webp&s=e9c3f157f56f6f84eb2c0334010669960c79387e', 'width': 1080}], 'source': {'height': 788, 'url': 'https://preview.redd.it/9d7bks86kh4e1.png?auto=webp&s=6ba4a89ff0ccbc5a57aae6a916f2b76867c74c2f', 'width': 1174}, 'variants': {}}]} |
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Qwq just witters on and on.... | 11 | I mean I enjoy some of it but if you ask qwq a coding/math question it just rambles on for page after page saying nothing of any interest and often going in what looks like circles. Is this a necessary part of the process to give a good answer in the end? | 2024-12-02T19:23:13 | https://www.reddit.com/r/LocalLLaMA/comments/1h5398o/qwq_just_witters_on_and_on/ | MrMrsPotts | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5398o | false | null | t3_1h5398o | /r/LocalLLaMA/comments/1h5398o/qwq_just_witters_on_and_on/ | false | false | self | 11 | null |
Huggingface is not an unlimited model storage anymore: new limit is 500 Gb per free account | 628 | 2024-12-02T19:50:12 | https://www.reddit.com/gallery/1h53x33 | Shir_man | reddit.com | 1970-01-01T00:00:00 | 0 | {} | 1h53x33 | false | null | t3_1h53x33 | /r/LocalLLaMA/comments/1h53x33/huggingface_is_not_an_unlimited_model_storage/ | false | false | 628 | null |
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Why didn't ONNX succeed in the LLM world? | 62 | ONNX has been around for a long time and is considered a standard for deploying deep learning models. It serves as both a format and a runtime inference engine. However, it appears to be falling behind LLM-specific inference runtimes like LLAMA.CPP (using the GGUF format). Why has this happened? Are there any technical limitations in ONNX that hinder its performance with common LLM architectures?
Downloads last month:
onnx-community/Llama-3.2-1B-Instruct => 821
bartowski/Llama-3.2-1B-Instruct-GGUF => 121227 | 2024-12-02T20:19:40 | https://www.reddit.com/r/LocalLLaMA/comments/1h54n1u/why_didnt_onnx_succeed_in_the_llm_world/ | graphitout | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h54n1u | false | null | t3_1h54n1u | /r/LocalLLaMA/comments/1h54n1u/why_didnt_onnx_succeed_in_the_llm_world/ | false | false | self | 62 | null |
Best writing model? (≈8b) | 1 | [removed] | 2024-12-02T20:21:52 | https://www.reddit.com/r/LocalLLaMA/comments/1h54p1d/best_writing_model_8b/ | Specialist_Theme8826 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h54p1d | false | null | t3_1h54p1d | /r/LocalLLaMA/comments/1h54p1d/best_writing_model_8b/ | false | false | self | 1 | null |
From Vector Search to Entity Processing: Evolving Zettelgarden's Connection Engine | 3 | 2024-12-02T20:28:45 | https://nsavage.substack.com/p/from-vector-search-to-entity-processing?r=rj3uw | Naga | nsavage.substack.com | 1970-01-01T00:00:00 | 0 | {} | 1h54v7g | false | null | t3_1h54v7g | /r/LocalLLaMA/comments/1h54v7g/from_vector_search_to_entity_processing_evolving/ | false | false | 3 | {'enabled': False, 'images': [{'id': 'X77OQjKgYoX7WkKS1FvCj5AtChuJBW3FwG4e65srIn0', 'resolutions': [{'height': 108, 'url': 'https://external-preview.redd.it/e0y6W8ZP1cUrm4u3iD7oSeIddrDy1o2pi9Jch0WFZfE.jpg?width=108&crop=smart&auto=webp&s=54c350e7cb5fc93f8bdd1c183cadfa7fc1f88346', 'width': 108}, {'height': 216, 'url': 'https://external-preview.redd.it/e0y6W8ZP1cUrm4u3iD7oSeIddrDy1o2pi9Jch0WFZfE.jpg?width=216&crop=smart&auto=webp&s=dfc218579df0a9e0e58277846b6d1c37cd779710', 'width': 216}, {'height': 320, 'url': 'https://external-preview.redd.it/e0y6W8ZP1cUrm4u3iD7oSeIddrDy1o2pi9Jch0WFZfE.jpg?width=320&crop=smart&auto=webp&s=0ca347e5e7d0d0b324b439d2ef88c10e5f3af082', 'width': 320}], 'source': {'height': 512, 'url': 'https://external-preview.redd.it/e0y6W8ZP1cUrm4u3iD7oSeIddrDy1o2pi9Jch0WFZfE.jpg?auto=webp&s=e89d2c4aaf2e9e8beff79700f55ed3c1b51fb650', 'width': 512}, 'variants': {}}]} |
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Linux AI enthousiasts, you might be slowly damaging your GPUs because of temperatures, without even knowing | 1 | \---
Here's a very short tutorial:
# To get which GPU ID corresponds to which GPU
nvtop
# List supported clocks
nvidia-smi -i "$gpu_id" -q -d SUPPORTED_CLOCKS
# Configure power limits
sudo nvidia-smi -i "$gpu_id" --power-limit "$power_limit"
# Configure gpu clock limits
sudo nvidia-smi -i "$gpu_id" --lock-gpu-clocks "0,$graphics_clock" --mode=1
# Configure memory clock limits
sudo nvidia-smi -i "$gpu_id" --lock-memory-clocks "0,$mem_clock"
Tip: you can remove `-i "$gpu_id"` to specify all GPUs.
\---
I hope this little story and tool will help some of you here.
Stay cool! | 2024-12-02T20:29:57 | https://www.reddit.com/r/LocalLLaMA/comments/1h54wa7/linux_ai_enthousiasts_you_might_be_slowly/ | TyraVex | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h54wa7 | false | null | t3_1h54wa7 | /r/LocalLLaMA/comments/1h54wa7/linux_ai_enthousiasts_you_might_be_slowly/ | false | false | self | 1 | null |
RIP finetuner / quanters. Are we going back to torrenting? | 173 | 2024-12-02T20:41:38 | Different_Fix_2217 | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1h556iw | false | null | t3_1h556iw | /r/LocalLLaMA/comments/1h556iw/rip_finetuner_quanters_are_we_going_back_to/ | false | false | 173 | {'enabled': True, 'images': [{'id': 'O6gREpx-zyoG-FRVMySp9nbA1hMqiz5dSXMOZTDQQNA', 'resolutions': [{'height': 141, 'url': 'https://preview.redd.it/xbqjfo1dyh4e1.png?width=108&crop=smart&auto=webp&s=ca17574f24abf19efbf6355e26f5df20e397cc70', 'width': 108}, {'height': 282, 'url': 'https://preview.redd.it/xbqjfo1dyh4e1.png?width=216&crop=smart&auto=webp&s=9125b06474d887c8f7bf0bf84c4c04fd19d16a7b', 'width': 216}, {'height': 418, 'url': 'https://preview.redd.it/xbqjfo1dyh4e1.png?width=320&crop=smart&auto=webp&s=e92b3f27cc9634333e3fd790dda7e8bf6e85f62b', 'width': 320}], 'source': {'height': 634, 'url': 'https://preview.redd.it/xbqjfo1dyh4e1.png?auto=webp&s=aaf07096365d1a79366bcbe66712954033070bb3', 'width': 485}, 'variants': {}}]} |
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eGPU on llama.cpp? | 4 | Hey so I think this question has been asked before but I've never found a guide.
For a thunderbolt eGPU on AMD/Linux x86\_64 how would one use the eGPU with llama.cpp with other local GPUs? | 2024-12-02T21:04:39 | https://www.reddit.com/r/LocalLLaMA/comments/1h55qyh/egpu_on_llamacpp/ | mayo551 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h55qyh | false | null | t3_1h55qyh | /r/LocalLLaMA/comments/1h55qyh/egpu_on_llamacpp/ | false | false | self | 4 | null |
I am noticing something not being taken into account in JP to EN Data sets | 2 | [removed] | 2024-12-02T21:11:31 | https://www.reddit.com/r/LocalLLaMA/comments/1h55x4u/i_am_noticing_something_not_being_taken_into/ | Oehriehqkbt | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h55x4u | false | null | t3_1h55x4u | /r/LocalLLaMA/comments/1h55x4u/i_am_noticing_something_not_being_taken_into/ | false | false | self | 2 | {'enabled': False, 'images': [{'id': 'dROJ8P7F4PhUWw6nsym9HkuS_crcn6Y_40Qk9nUOTrQ', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=108&crop=smart&auto=webp&s=5e126aab35df6f7a1cabaff2403ce2bf73eb0b25', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=216&crop=smart&auto=webp&s=517c479b1798541828fb521c85dd02943b705586', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=320&crop=smart&auto=webp&s=0e6d57056506f8ffd2547ffed80f93088ae8d060', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=640&crop=smart&auto=webp&s=31827c372f3fa6f36815da461afcffeb4d5990d3', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=960&crop=smart&auto=webp&s=553236c4b1663c341c287466062f8a14cd22977d', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=1080&crop=smart&auto=webp&s=658cf77a23c3c154327cc84b2021c0469495ac23', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?auto=webp&s=eaf6c5babc69df78263d3a2bff70dad1d779dac8', 'width': 1200}, 'variants': {}}]} |
What is your favorite model currently? | 90 | I've been really digging Supernova Medius 14b lately. It's super speedy on my M4 Pro, and it outperforms the standard Qwen2.5 14b for me. The responses are more accurate and better organized too. I tried it with some coding tasks, and while Qwen2.5 Coder 14b did a bit better with those, Supernova Medius is great for general stuff. For its size, it's pretty impressive. What about you? Is there a model that really stands out to you based on its type and size? | 2024-12-02T21:33:01 | https://www.reddit.com/r/LocalLLaMA/comments/1h56g5s/what_is_your_favorite_model_currently/ | Sky_Linx | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h56g5s | false | null | t3_1h56g5s | /r/LocalLLaMA/comments/1h56g5s/what_is_your_favorite_model_currently/ | false | false | self | 90 | null |
Locally hosted LLM for data analysis, but data is too BIG | 2 | Hello there,
I am currently trying to use self hosted Llama or Mistral to answer questions about some data that I own,
The data are either in .csv or .json, and the natural of questions are basically like SQL query in the form of natural language.
However I notice that I am heavily limited by the size of the data, as I can't pass along the serialized data as string as they mostly will exceed the allowed token limits, and when I force it, the LLM behaves like a drunk person by starting to ramble about topics that are not related, or just flat out gives non sense response.
Some of the possible solutions that I'v seen people talked about is to either:
\-Store the data else where instead of passing them along with my prompt, and somehow make the LLM access it
\-or Break the data in batch and do multiple upload to LLM (no idea how to achieve this)
can someone give me some hint? any tips are appreciated.
Thank you | 2024-12-02T21:48:15 | https://www.reddit.com/r/LocalLLaMA/comments/1h56th1/locally_hosted_llm_for_data_analysis_but_data_is/ | zkkzkk32312 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h56th1 | false | null | t3_1h56th1 | /r/LocalLLaMA/comments/1h56th1/locally_hosted_llm_for_data_analysis_but_data_is/ | false | false | self | 2 | null |
AI Linux entousiasts running RTX GPUs, your cards can overheat without reporting it | 209 | Hello LocalLLaMa!
I realized last week that my 3090 was running way too hot, without even being aware about it.
This happened for almost 6 months because the Nvidia drivers for Linux do not expose the VRAM or junctions temperatures, so I couldn't monitor my GPUs properly. Btw, the throttle limit for these components is 105°C, which is way too hot to be healthy.
Looking online, there is a [3 years old post](https://forums.developer.nvidia.com/t/request-gpu-memory-junction-temperature-via-nvidia-smi-or-nvml-api/168346/145) about this on Nvidia's forums, accumulating over 350 comments and 85k views. Unfortunately, nothing good came out of it.
As an answer, someone created [https://github.com/olealgoritme/gddr6](https://github.com/olealgoritme/gddr6), which accesses "undocumented GPU registers via direct PCIe reads" to get VRAM temperatures. Nice.
But even with VRAM temps being now under control, the poor GPU still crashed under heavy AI workloads. Perhaps the junction temp was too hot? Well, how could I know?
Luckily, someone else forked the previous project and added junctions temperatures readings: [https://github.com/jjziets/gddr6\_temps](https://github.com/jjziets/gddr6_temps). Buuuuut it wasn't compiling, and seemed too complex for the common man.
So last weekend I inspired myself from that repo and made this:
[https:\/\/github.com\/ThomasBaruzier\/gddr6-core-junction-vram-temps](https://preview.redd.it/qjx1qoeyai4e1.png?width=368&format=png&auto=webp&s=3358b8a2ed9849b80818b14aab73ff401d7b8232)
It's a little CLI program reading all the temps. So you now know if your card is cooking or not!
Funnily enough, mine did, at around 105-110°C... There is obviously something wrong with my card, I'll have to take it apart another day, but this is so stupid to learn that, this way.
\---
If you find out your GPU is also overheating, here's a quick tutorial to power limit it:
# To get which GPU ID corresponds to which GPU
nvtop
# List supported clocks
nvidia-smi -i "$gpu_id" -q -d SUPPORTED_CLOCKS
# Configure power limits
sudo nvidia-smi -i "$gpu_id" --power-limit "$power_limit"
# Configure gpu clock limits
sudo nvidia-smi -i "$gpu_id" --lock-gpu-clocks "0,$graphics_clock" --mode=1
# Configure memory clock limits
sudo nvidia-smi -i "$gpu_id" --lock-memory-clocks "0,$mem_clock"
Tip: you can remove -i "$gpu\_id" to specify all GPUs.
\---
I hope this little story and tool will help some of you here.
Stay cool! | 2024-12-02T21:54:06 | https://www.reddit.com/r/LocalLLaMA/comments/1h56yko/ai_linux_entousiasts_running_rtx_gpus_your_cards/ | TyraVex | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h56yko | false | null | t3_1h56yko | /r/LocalLLaMA/comments/1h56yko/ai_linux_entousiasts_running_rtx_gpus_your_cards/ | false | false | 209 | {'enabled': False, 'images': [{'id': 'hnZDIk_TY24WLB527CbQAHCEEc09FIgy3quBz_-6dgo', 'resolutions': [{'height': 57, 'url': 'https://external-preview.redd.it/ae0Qo8Vt7zK3YN5EJj9DVaScMl5RBOblsHS-0BEDVxs.jpg?width=108&crop=smart&auto=webp&s=3203a37a03ac29dcb77bd0264ffded36cc9eb3e8', 'width': 108}], 'source': {'height': 80, 'url': 'https://external-preview.redd.it/ae0Qo8Vt7zK3YN5EJj9DVaScMl5RBOblsHS-0BEDVxs.jpg?auto=webp&s=119b7279fd124a86be1ec5ae8f58e06b3fca19a8', 'width': 150}, 'variants': {}}]} |
|
Rocking a Mac Studio M2 192gb, is there anything better than Mistral Large / Qwen 2.5 72gb these days? | 4 | I have to process a few hundred documents overnight and have not been messing with local models much in the last few months. Are Mistral Large and Qwen 2.5 still reigning supreme? | 2024-12-02T21:58:51 | https://www.reddit.com/r/LocalLLaMA/comments/1h572mu/rocking_a_mac_studio_m2_192gb_is_there_anything/ | Berberis | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h572mu | false | null | t3_1h572mu | /r/LocalLLaMA/comments/1h572mu/rocking_a_mac_studio_m2_192gb_is_there_anything/ | false | false | self | 4 | null |
How I leaked the V0 System Prompts (Video Explanation) | 33 | Here is a short video explanation of how I got to these system prompts and why I decided to share them with the community.
I've attached the one of the Jailbreak prompts that you can use to get these, and I suggest you explore the system yourself and try to draw what conclusions you can from it.
Like I said, I have never seen hallucinations of this nature. I have been around the block and done my fair share of model exploration from the days of gpt2 up until now.
Let me know what ya'll think, how you imagine this system works under the hood and maybe what you would like to see in the future regarding this project. | 2024-12-02T22:16:25 | https://www.reddit.com/r/LocalLLaMA/comments/1h57hur/how_i_leaked_the_v0_system_prompts_video/ | Odd-Environment-7193 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h57hur | false | null | t3_1h57hur | /r/LocalLLaMA/comments/1h57hur/how_i_leaked_the_v0_system_prompts_video/ | false | false | self | 33 | {'enabled': False, 'images': [{'id': 'ZVniVBxKIs7g5pDUt532aH_TzvUqwMJI5rBfyzrNR78', 'resolutions': [{'height': 81, 'url': 'https://external-preview.redd.it/iTGSLV7xryfD3Mr1IZOlJdw1Te0oIO-HjmAWr-I3-MY.jpg?width=108&crop=smart&auto=webp&s=401eb72a316804c38e1b2ac9b6e11e52552277ec', 'width': 108}, {'height': 162, 'url': 'https://external-preview.redd.it/iTGSLV7xryfD3Mr1IZOlJdw1Te0oIO-HjmAWr-I3-MY.jpg?width=216&crop=smart&auto=webp&s=e453bf7a1bae98aad44ef0e16703d90a6f45567d', 'width': 216}, {'height': 240, 'url': 'https://external-preview.redd.it/iTGSLV7xryfD3Mr1IZOlJdw1Te0oIO-HjmAWr-I3-MY.jpg?width=320&crop=smart&auto=webp&s=bb005ab6d1b8ac1a7025486f53007d4232e7019a', 'width': 320}], 'source': {'height': 360, 'url': 'https://external-preview.redd.it/iTGSLV7xryfD3Mr1IZOlJdw1Te0oIO-HjmAWr-I3-MY.jpg?auto=webp&s=48f4480e7f34662a5cd96ff3c8eb388934da6643', 'width': 480}, 'variants': {}}]} |
Best LLM for natural language to SQL queries? | 1 | [removed] | 2024-12-02T22:49:40 | https://www.reddit.com/r/LocalLLaMA/comments/1h589x5/best_llm_for_natural_language_to_sql_queries/ | Top-Square3799 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h589x5 | false | null | t3_1h589x5 | /r/LocalLLaMA/comments/1h589x5/best_llm_for_natural_language_to_sql_queries/ | false | false | self | 1 | null |
Has anyone built their own layer for orchestrating how LLM should use tools? | 2 | So at the moment,
1. we send messages to the model and describe which tools are available
2. the model makes a decision which tools to use
3. we execute them
4. give model the results
5. model produces the final response
However, the steps 2 is a complete black box, and also highly dependent on that model's capabilities.
Has anyone experimented with building their own logic for tool planning and discovery? are there existing frameworks for that? | 2024-12-02T22:52:44 | https://www.reddit.com/r/LocalLLaMA/comments/1h58cc3/has_anyone_built_their_own_layer_for/ | punkpeye | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h58cc3 | false | null | t3_1h58cc3 | /r/LocalLLaMA/comments/1h58cc3/has_anyone_built_their_own_layer_for/ | false | false | self | 2 | null |
Building the cheapest API for everyone. LTX-Video model supported and completely free! | 1 | [removed] | 2024-12-02T23:20:03 | https://www.reddit.com/r/LocalLLaMA/comments/1h58z6q/building_the_cheapest_api_for_everyone_ltxvideo/ | Ok_Difference_4483 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h58z6q | false | null | t3_1h58z6q | /r/LocalLLaMA/comments/1h58z6q/building_the_cheapest_api_for_everyone_ltxvideo/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'wZYm8nhsA5pD7NplL5-OgBvi3pHqqPix8-HFbNWi13g', 'resolutions': [{'height': 60, 'url': 'https://external-preview.redd.it/uZN_zKYB96EDTmuc3PU6Ntya2LXZJkxHmG0NxKbHIAw.jpg?width=108&crop=smart&auto=webp&s=258ed84cf9858c878f961d2ca891c571e975ea99', 'width': 108}, {'height': 121, 'url': 'https://external-preview.redd.it/uZN_zKYB96EDTmuc3PU6Ntya2LXZJkxHmG0NxKbHIAw.jpg?width=216&crop=smart&auto=webp&s=3f1978a271aeba766ee9a396652bcab45908b895', 'width': 216}, {'height': 180, 'url': 'https://external-preview.redd.it/uZN_zKYB96EDTmuc3PU6Ntya2LXZJkxHmG0NxKbHIAw.jpg?width=320&crop=smart&auto=webp&s=7130b28d2415f00d4ae40c349807cfae57adb908', 'width': 320}], 'source': {'height': 288, 'url': 'https://external-preview.redd.it/uZN_zKYB96EDTmuc3PU6Ntya2LXZJkxHmG0NxKbHIAw.jpg?auto=webp&s=496ac5414823ce50932033827644899f1cb6c60d', 'width': 512}, 'variants': {}}]} |
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Extractous - Fast Text Extraction for GenAI with Rust + Apache Tika | 29 | 2024-12-02T23:38:46 | https://github.com/yobix-ai/extractous | davidmezzetti | github.com | 1970-01-01T00:00:00 | 0 | {} | 1h59eao | false | null | t3_1h59eao | /r/LocalLLaMA/comments/1h59eao/extractous_fast_text_extraction_for_genai_with/ | false | false | 29 | {'enabled': False, 'images': [{'id': 'e4qltneGpO10JM8YAxDMpNVHY-g4tVZc59KRNOKJdGw', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/2ZZfg34J3XCT-70NiYC5zQGR1rhgaj4zFGVXKLWmSyU.jpg?width=108&crop=smart&auto=webp&s=38526efa5ae0240683f9cbe0c5ea9faae24f43f5', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/2ZZfg34J3XCT-70NiYC5zQGR1rhgaj4zFGVXKLWmSyU.jpg?width=216&crop=smart&auto=webp&s=53768c530d8d5c74a421c29131b3d8d3a46e58f4', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/2ZZfg34J3XCT-70NiYC5zQGR1rhgaj4zFGVXKLWmSyU.jpg?width=320&crop=smart&auto=webp&s=e0c045ba58834dbc00d75246eb0b974fd8b556e0', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/2ZZfg34J3XCT-70NiYC5zQGR1rhgaj4zFGVXKLWmSyU.jpg?width=640&crop=smart&auto=webp&s=9fc36578a3ee0cbcd1e0729a94c5b0f7519287a8', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/2ZZfg34J3XCT-70NiYC5zQGR1rhgaj4zFGVXKLWmSyU.jpg?width=960&crop=smart&auto=webp&s=2601096261829018374edfb15489c14ad804446c', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/2ZZfg34J3XCT-70NiYC5zQGR1rhgaj4zFGVXKLWmSyU.jpg?width=1080&crop=smart&auto=webp&s=890bfe10a212ae5e3d676343c526739c937b2873', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/2ZZfg34J3XCT-70NiYC5zQGR1rhgaj4zFGVXKLWmSyU.jpg?auto=webp&s=c8be8c1e00001c8ed9c87661fa77bfd567ddb1b5', 'width': 1200}, 'variants': {}}]} |
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What are the use cases of smaller models (<3B) these days? | 10 | So far, for most of my personal or work projects, I've been using 32B+ models, but I've never actually used models <3B for something meaningful. Some of them are targeted to run on-device, but I don't really know which tasks do these models excel at in those environments.
Whenever I try them on LMStudio, they output gibberish or are extremely verbose if not strictly controlled by the sampling params.
Does anyone have some use cases for them? I'd like to know some great use cases since I know nothing about this area. | 2024-12-02T23:55:00 | https://www.reddit.com/r/LocalLLaMA/comments/1h59r58/what_are_the_use_cases_of_smaller_models_3b_these/ | Odd_Tumbleweed574 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h59r58 | false | null | t3_1h59r58 | /r/LocalLLaMA/comments/1h59r58/what_are_the_use_cases_of_smaller_models_3b_these/ | false | false | self | 10 | null |
Llama 70b Multi-step tool implementation | 9 | Has anyone successfully implemented Multi-step tool calling in a model of this size? If you have, I would be curious to hear how you did.
I’ve got it working in a couple examples through vigorous prompting but am unsatisfied with the results as they are inconsistent. | 2024-12-03T00:51:46 | https://www.reddit.com/r/LocalLLaMA/comments/1h5azbt/llama_70b_multistep_tool_implementation/ | Disastrous_Ad8959 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5azbt | false | null | t3_1h5azbt | /r/LocalLLaMA/comments/1h5azbt/llama_70b_multistep_tool_implementation/ | false | false | self | 9 | null |
How can I run more than 5 Google Gemini API keys on a single computer | 1 | [removed] | 2024-12-03T01:03:53 | https://www.reddit.com/r/LocalLLaMA/comments/1h5b8og/how_can_i_run_more_than_5_google_gemini_api_keys/ | Fluffy-Cold-1727 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5b8og | false | null | t3_1h5b8og | /r/LocalLLaMA/comments/1h5b8og/how_can_i_run_more_than_5_google_gemini_api_keys/ | false | false | self | 1 | null |
Llama.cpp Vulkan on AMD BC-250 | 1 | [removed] | 2024-12-03T01:20:11 | https://www.reddit.com/r/LocalLLaMA/comments/1h5bl65/llamacpp_vulkan_on_amd_bc250/ | MachineZer0 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5bl65 | false | null | t3_1h5bl65 | /r/LocalLLaMA/comments/1h5bl65/llamacpp_vulkan_on_amd_bc250/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'OgFzGCIRw1ZxjMOSkfV1OiH-_nQiZl8rzSonmOAuhGs', 'resolutions': [{'height': 108, 'url': 'https://external-preview.redd.it/P8lS0kk6BFe2IEo6TxCZd1LVwksc34IkzGTVx_SCc8w.jpg?width=108&crop=smart&auto=webp&s=3d74dbe4f1d67cc8b587db9aa01762f26e269bcf', 'width': 108}], 'source': {'height': 150, 'url': 'https://external-preview.redd.it/P8lS0kk6BFe2IEo6TxCZd1LVwksc34IkzGTVx_SCc8w.jpg?auto=webp&s=b9f5c4e4867fbffb2c1ff45dd70aa338d1e3f40c', 'width': 150}, 'variants': {}}]} |
Is there anything that you can do with 48GB that you can't do with 24GB? | 1 | [removed] | 2024-12-03T01:40:43 | https://www.reddit.com/r/LocalLLaMA/comments/1h5c08d/is_there_anything_that_you_can_do_with_48gb_that/ | 7evenate9ine | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5c08d | false | null | t3_1h5c08d | /r/LocalLLaMA/comments/1h5c08d/is_there_anything_that_you_can_do_with_48gb_that/ | false | false | self | 1 | null |
Great for AMD GPUs | 98 | This is yuge. Believe me. | 2024-12-03T02:46:19 | https://embeddedllm.com/blog/vllm-now-supports-running-gguf-on-amd-radeon-gpu | badabimbadabum2 | embeddedllm.com | 1970-01-01T00:00:00 | 0 | {} | 1h5dbek | false | null | t3_1h5dbek | /r/LocalLLaMA/comments/1h5dbek/great_for_amd_gpus/ | false | false | 98 | {'enabled': False, 'images': [{'id': 'yI7hvK0q8OkFyANHxWNLT4KJpno1apRxdEcPmZxQ6vE', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/usHNFQFap_sWW0pp7gnh3u0U4qsVCeerbupPg52bvMc.jpg?width=108&crop=smart&auto=webp&s=3d270a3bc587e694da6f910c806bd87bdfbf9ee8', 'width': 108}, {'height': 117, 'url': 'https://external-preview.redd.it/usHNFQFap_sWW0pp7gnh3u0U4qsVCeerbupPg52bvMc.jpg?width=216&crop=smart&auto=webp&s=7c7ff026979d86a7651e96d03db0f0954983788f', 'width': 216}, {'height': 174, 'url': 'https://external-preview.redd.it/usHNFQFap_sWW0pp7gnh3u0U4qsVCeerbupPg52bvMc.jpg?width=320&crop=smart&auto=webp&s=39394e3c31f378f976d05248ad603eb07a0aaf36', 'width': 320}], 'source': {'height': 192, 'url': 'https://external-preview.redd.it/usHNFQFap_sWW0pp7gnh3u0U4qsVCeerbupPg52bvMc.jpg?auto=webp&s=07d3f95423b993ce77de2cfcbcf5055aa23d63e3', 'width': 352}, 'variants': {}}]} |
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Tricks for DPO tuning a Code LLM, Part 1 - Logit Curriculum Learning | 15 | 2024-12-03T03:05:54 | https://brianfitzgerald.xyz/dpo-pruning/ | sonderemawe | brianfitzgerald.xyz | 1970-01-01T00:00:00 | 0 | {} | 1h5dp07 | false | null | t3_1h5dp07 | /r/LocalLLaMA/comments/1h5dp07/tricks_for_dpo_tuning_a_code_llm_part_1_logit/ | false | false | default | 15 | null |
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Would you rather fight a 70B model or 70 1B models? | 234 | Let's assume these 1B models are able to reason with each other.
Which one are you taking on? | 2024-12-03T03:28:02 | https://www.reddit.com/r/LocalLLaMA/comments/1h5e47c/would_you_rather_fight_a_70b_model_or_70_1b_models/ | LewisTheScot | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5e47c | false | null | t3_1h5e47c | /r/LocalLLaMA/comments/1h5e47c/would_you_rather_fight_a_70b_model_or_70_1b_models/ | false | false | self | 234 | null |
this sub lately | 1 | 2024-12-03T03:39:45 | PortlandPoly | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1h5ec2d | false | null | t3_1h5ec2d | /r/LocalLLaMA/comments/1h5ec2d/this_sub_lately/ | false | false | 1 | {'enabled': True, 'images': [{'id': '9M4gbSPjJCQ9Ki7bxnBdky0lvVijvqMepmhfe86olhI', 'resolutions': [{'height': 109, 'url': 'https://preview.redd.it/rwdil8px0k4e1.png?width=108&crop=smart&auto=webp&s=f81d84e3bec1bce0f5ef6c7e12783e60ac9017c5', 'width': 108}, {'height': 219, 'url': 'https://preview.redd.it/rwdil8px0k4e1.png?width=216&crop=smart&auto=webp&s=b2e4f515b00b948cc05f65b20a3cffd49b09551b', 'width': 216}, {'height': 324, 'url': 'https://preview.redd.it/rwdil8px0k4e1.png?width=320&crop=smart&auto=webp&s=2998f5523826d190152cf03eb5ba7c688c547291', 'width': 320}, {'height': 649, 'url': 'https://preview.redd.it/rwdil8px0k4e1.png?width=640&crop=smart&auto=webp&s=317804d1e38ea0c3242433d107a22d87e181eec0', 'width': 640}, {'height': 974, 'url': 'https://preview.redd.it/rwdil8px0k4e1.png?width=960&crop=smart&auto=webp&s=13f8011add665df5f974ed168f805d0e575f19c8', 'width': 960}, {'height': 1096, 'url': 'https://preview.redd.it/rwdil8px0k4e1.png?width=1080&crop=smart&auto=webp&s=5654554e0b3577d2102a02a1db31dfcdf8c0acc6', 'width': 1080}], 'source': {'height': 1141, 'url': 'https://preview.redd.it/rwdil8px0k4e1.png?auto=webp&s=96d836c82451f4c34a279234b8ae85e9a01e6c47', 'width': 1124}, 'variants': {}}]} |
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MCP 🤝 OpenAI Bridge: Run MCP Tools with Any OpenAI-Compatible LLM | 14 | Hey r/LocalLLaMA fellas,
I created an MCP implementation that bridges the gap between MCP servers (and tools) and OpenAI's function calling interface. I needed to use MCP tools with OpenAI's API and local models, and couldn't find an existing solution that worked.
While it's primarily designed for use with the OpenAI API, you can also use it with Ollama running locally, LM Studio, or any endpoint that implements the OpenAI API spec.
I've put the code up on GitHub [here](https://github.com/bartolli/mcp-llm-bridge). Let me know what you think or if you have any questions! | 2024-12-03T03:42:02 | https://www.reddit.com/r/LocalLLaMA/comments/1h5edl7/mcp_openai_bridge_run_mcp_tools_with_any/ | Plenty_Seesaw8878 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5edl7 | false | null | t3_1h5edl7 | /r/LocalLLaMA/comments/1h5edl7/mcp_openai_bridge_run_mcp_tools_with_any/ | false | false | self | 14 | {'enabled': False, 'images': [{'id': 'iPXmFlc8EK4kUP3A4Ci2yEa5-l1QdIO5chXWry0taog', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/rj2GsEs0W7LA51cOuv6oB_6R73BJfQskqHzphoOgy5A.jpg?width=108&crop=smart&auto=webp&s=c5cee3a40a35c30209f822c74f756235206a2f13', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/rj2GsEs0W7LA51cOuv6oB_6R73BJfQskqHzphoOgy5A.jpg?width=216&crop=smart&auto=webp&s=aaa1bcaf0455616bf83436e04f0ac5f192751f59', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/rj2GsEs0W7LA51cOuv6oB_6R73BJfQskqHzphoOgy5A.jpg?width=320&crop=smart&auto=webp&s=626737493fd5906ea675fc21234f718d50ad5bc9', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/rj2GsEs0W7LA51cOuv6oB_6R73BJfQskqHzphoOgy5A.jpg?width=640&crop=smart&auto=webp&s=0253403aaddc575434d004c18572a5109faba70c', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/rj2GsEs0W7LA51cOuv6oB_6R73BJfQskqHzphoOgy5A.jpg?width=960&crop=smart&auto=webp&s=1754ecb9282475915b9397492e429eae124b69f3', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/rj2GsEs0W7LA51cOuv6oB_6R73BJfQskqHzphoOgy5A.jpg?width=1080&crop=smart&auto=webp&s=ee623834becdf3871d6979f5335a2780dbd523d4', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/rj2GsEs0W7LA51cOuv6oB_6R73BJfQskqHzphoOgy5A.jpg?auto=webp&s=fb00cf1c93ecf5380ebeabacda6d1162b50fd123', 'width': 1200}, 'variants': {}}]} |
Writing Assistant & Document Access | 1 | [removed] | 2024-12-03T03:57:25 | https://www.reddit.com/r/LocalLLaMA/comments/1h5enq8/writing_assistant_document_access/ | papacholo | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5enq8 | false | null | t3_1h5enq8 | /r/LocalLLaMA/comments/1h5enq8/writing_assistant_document_access/ | false | false | self | 1 | null |
Llama is a | 1 |
[View Poll](https://www.reddit.com/poll/1h5erbo) | 2024-12-03T04:02:36 | https://www.reddit.com/r/LocalLLaMA/comments/1h5erbo/llama_is_a/ | Dismal_Spread5596 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5erbo | false | null | t3_1h5erbo | /r/LocalLLaMA/comments/1h5erbo/llama_is_a/ | false | false | self | 1 | null |
Vercel SDK – how do I instruct which tool to use? | 1 | https://github.com/vercel/ai/issues/3944
basically this question | 2024-12-03T04:03:09 | https://www.reddit.com/r/LocalLLaMA/comments/1h5erpi/vercel_sdk_how_do_i_instruct_which_tool_to_use/ | punkpeye | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5erpi | false | null | t3_1h5erpi | /r/LocalLLaMA/comments/1h5erpi/vercel_sdk_how_do_i_instruct_which_tool_to_use/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': '_XlC-u0Dz1BMpmnNSQPwtgANajTtELjMIa1xeKxSZpo', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/f-S2k7c_h1lkm6WILPyhGsGIQSIHNrxu7WnUEec-_M4.jpg?width=108&crop=smart&auto=webp&s=575d500a8e78e4ec693fdafb616e6555a7252ea9', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/f-S2k7c_h1lkm6WILPyhGsGIQSIHNrxu7WnUEec-_M4.jpg?width=216&crop=smart&auto=webp&s=1fc63475958b6c5a42f93c840afc1332920957b5', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/f-S2k7c_h1lkm6WILPyhGsGIQSIHNrxu7WnUEec-_M4.jpg?width=320&crop=smart&auto=webp&s=b9f2bae4f5398b335c11329ffa80d38e8368bdc5', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/f-S2k7c_h1lkm6WILPyhGsGIQSIHNrxu7WnUEec-_M4.jpg?width=640&crop=smart&auto=webp&s=aa4f795f1dc908d70eb12ebd5cdc375043ecdbc5', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/f-S2k7c_h1lkm6WILPyhGsGIQSIHNrxu7WnUEec-_M4.jpg?width=960&crop=smart&auto=webp&s=f0e9bf0923f37df68c06457d6689bf63bb6500cc', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/f-S2k7c_h1lkm6WILPyhGsGIQSIHNrxu7WnUEec-_M4.jpg?width=1080&crop=smart&auto=webp&s=a1ca7bffa63734636f28f2e6aa07ecb8fc741f99', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/f-S2k7c_h1lkm6WILPyhGsGIQSIHNrxu7WnUEec-_M4.jpg?auto=webp&s=14a76fc7423c20445455407dcabf14e3e5099a3e', 'width': 1200}, 'variants': {}}]} |
LM Studio running on NPU, finally! (Qualcomm Snapdragon's Copilot+ PC ) | 170 | 2024-12-03T04:13:08 | https://v.redd.it/sfvpeevj6k4e1 | geringonco | /r/LocalLLaMA/comments/1h5eyb8/lm_studio_running_on_npu_finally_qualcomm/ | 1970-01-01T00:00:00 | 0 | {} | 1h5eyb8 | false | {'reddit_video': {'bitrate_kbps': 1200, 'dash_url': 'https://v.redd.it/sfvpeevj6k4e1/DASHPlaylist.mpd?a=1735920821%2CMTEyY2QwYTYzODk1NzA0ZGIwMzY1MzFjYjg3NTU4NzNhMWRhNWM5MDU3NDRlZDhiNTVjNTRjODVkZjk1ZDQ4Mw%3D%3D&v=1&f=sd', 'duration': 151, 'fallback_url': 'https://v.redd.it/sfvpeevj6k4e1/DASH_480.mp4?source=fallback', 'has_audio': True, 'height': 854, 'hls_url': 'https://v.redd.it/sfvpeevj6k4e1/HLSPlaylist.m3u8?a=1735920821%2CZGRiYTk5ZDM3Y2VhYTJmYzM0MGIzZjAyZGUzN2I3YWFkMzE3MWEzYzJkZGE2MGQ0NDVlNTI4ZDY3ZWQ1MTJmMw%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/sfvpeevj6k4e1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 480}} | t3_1h5eyb8 | /r/LocalLLaMA/comments/1h5eyb8/lm_studio_running_on_npu_finally_qualcomm/ | false | false | 170 | {'enabled': False, 'images': [{'id': 'bmRyZ2Fkdmo2azRlMckDta8F54n8eWGrX0MHmWltl3AHKcni1zxTkvOcppMF', 'resolutions': [{'height': 192, 'url': 'https://external-preview.redd.it/bmRyZ2Fkdmo2azRlMckDta8F54n8eWGrX0MHmWltl3AHKcni1zxTkvOcppMF.png?width=108&crop=smart&format=pjpg&auto=webp&s=e692c6010193a9aa8ce07a657efb752619f5c287', 'width': 108}, {'height': 384, 'url': 'https://external-preview.redd.it/bmRyZ2Fkdmo2azRlMckDta8F54n8eWGrX0MHmWltl3AHKcni1zxTkvOcppMF.png?width=216&crop=smart&format=pjpg&auto=webp&s=d528c4ca9eae423d56fdb87ed38f0435d5797e38', 'width': 216}, {'height': 569, 'url': 'https://external-preview.redd.it/bmRyZ2Fkdmo2azRlMckDta8F54n8eWGrX0MHmWltl3AHKcni1zxTkvOcppMF.png?width=320&crop=smart&format=pjpg&auto=webp&s=118cf7eb865ff97e6ed681aeda8fb0a06937c135', 'width': 320}, {'height': 1138, 'url': 'https://external-preview.redd.it/bmRyZ2Fkdmo2azRlMckDta8F54n8eWGrX0MHmWltl3AHKcni1zxTkvOcppMF.png?width=640&crop=smart&format=pjpg&auto=webp&s=f06bba122d70bd83d3301c805026a0a5c0cc20ad', 'width': 640}], 'source': {'height': 1138, 'url': 'https://external-preview.redd.it/bmRyZ2Fkdmo2azRlMckDta8F54n8eWGrX0MHmWltl3AHKcni1zxTkvOcppMF.png?format=pjpg&auto=webp&s=cc0986a8091c29077c2951bc84593e591e6b83fe', 'width': 640}, 'variants': {}}]} |
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Prompt Caching in OSS models | 1 | [removed] | 2024-12-03T04:44:45 | https://www.reddit.com/r/LocalLLaMA/comments/1h5fhxe/prompt_caching_in_oss_models/ | Winter-Seesaw6919 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5fhxe | false | null | t3_1h5fhxe | /r/LocalLLaMA/comments/1h5fhxe/prompt_caching_in_oss_models/ | false | false | self | 1 | null |
I built a simple Character AI-like UI after my previous post asking for recommendations | 26 | Hey everyone! A few weeks ago, I [Looking for an open-source Character AI-like UI for deploying a fine-tuned RP model](https://www.reddit.com/r/LocalLLaMA/comments/1gt4x3l/looking_for_an_opensource_character_ailike_ui_for/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button) looking for an open-source Character AI-like UI for my fine-tuned RP model. Since I couldn't find exactly what I needed, I decided to build one myself with Claude's help!
## Features
- 💬 Continuous chat with history
- 🔄 Retry/regenerate messages while keeping chat history
- 📝 Create multiple chat sessions
- 🤖 Compatible with all OpenAI API spec endpoints
- 👤 Character/role editing
- ✏️ Edit/delete messages (both assistant & user)
- 💾 Import/export configurations
- 📱 Mobile responsive
## Tech Stack
- Vue 3 + TypeScript
- Element Plus
- Yarn
# Why I Built This
After my previous post, I realized most existing solutions were either too complex or missing key features I wanted. I aimed to create something simple yet functional that others could easily modify and use.
# Try It Out
The project is open source and available on GitHub: [mirau-chat-ui](https://github.com/woshixiaobai2019/mirau-chat-ui)
## What's Next
I'm planning to open-source my fine-tuned RP model soon!(A o1-like RP model) It's been performing really well in testing, and I think it would be great to share it with the community. Stay tuned for updates on that.
The model combined with this UI should provide a complete solution for anyone looking to set up their own RP chat system.
Feel free to try out the UI and let me know what you think! PRs and suggestions are welcome. | 2024-12-03T06:02:27 | https://www.reddit.com/r/LocalLLaMA/comments/1h5gtfj/i_built_a_simple_character_ailike_ui_after_my/ | EliaukMouse | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5gtfj | false | null | t3_1h5gtfj | /r/LocalLLaMA/comments/1h5gtfj/i_built_a_simple_character_ailike_ui_after_my/ | false | false | self | 26 | {'enabled': False, 'images': [{'id': 'PJOmbrjautjsuFyuoj8ugHojfWuSpJZGwHbeOPCOMXE', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/FAe9KqqZyxIj7KAzKQO7N5eloHaGMbXkyYf5_QFO5Ok.jpg?width=108&crop=smart&auto=webp&s=cfdd866214580db0339d75e00dd40c1e32addeed', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/FAe9KqqZyxIj7KAzKQO7N5eloHaGMbXkyYf5_QFO5Ok.jpg?width=216&crop=smart&auto=webp&s=05368623e725e2505bd7b6599c0bc316ab38fcdd', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/FAe9KqqZyxIj7KAzKQO7N5eloHaGMbXkyYf5_QFO5Ok.jpg?width=320&crop=smart&auto=webp&s=8d409e82a9540dfcbb99e49b3629c565384a5bea', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/FAe9KqqZyxIj7KAzKQO7N5eloHaGMbXkyYf5_QFO5Ok.jpg?width=640&crop=smart&auto=webp&s=0733aa9d3ad529947a915bd23636b54d7cc9f4c8', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/FAe9KqqZyxIj7KAzKQO7N5eloHaGMbXkyYf5_QFO5Ok.jpg?width=960&crop=smart&auto=webp&s=4623cd896e0e9fb1f4d865d03e9bb27d268a8cdc', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/FAe9KqqZyxIj7KAzKQO7N5eloHaGMbXkyYf5_QFO5Ok.jpg?width=1080&crop=smart&auto=webp&s=13775114345f442eb2dc616247855b50bcb3986c', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/FAe9KqqZyxIj7KAzKQO7N5eloHaGMbXkyYf5_QFO5Ok.jpg?auto=webp&s=62afb39cd9490681e3f77e3c7a3b61590e75ab14', 'width': 1200}, 'variants': {}}]} |
Can i change the llama.cpp version used by lm studio myself? | 9 | lm studio has its moods, it updates when it wants to, which may not coincide with when i want it to update. I was thinking, can the llama.cpp version used by lm studio be replaced by a newer version manually without help of its developers? | 2024-12-03T06:20:53 | https://www.reddit.com/r/LocalLLaMA/comments/1h5h3lp/can_i_change_the_llamacpp_version_used_by_lm/ | ab2377 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5h3lp | false | null | t3_1h5h3lp | /r/LocalLLaMA/comments/1h5h3lp/can_i_change_the_llamacpp_version_used_by_lm/ | false | false | self | 9 | null |
What can I do with 8xA800 cards? | 1 | [removed] | 2024-12-03T06:25:17 | https://www.reddit.com/r/LocalLLaMA/comments/1h5h5xu/what_can_i_do_with_8xa800_cards/ | VariationStreet2332 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5h5xu | false | null | t3_1h5h5xu | /r/LocalLLaMA/comments/1h5h5xu/what_can_i_do_with_8xa800_cards/ | false | false | self | 1 | null |
What can I do with 8xA800 cards? | 1 | [removed] | 2024-12-03T06:28:05 | https://www.reddit.com/r/LocalLLaMA/comments/1h5h7cw/what_can_i_do_with_8xa800_cards/ | CrazyShipTed | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5h7cw | false | null | t3_1h5h7cw | /r/LocalLLaMA/comments/1h5h7cw/what_can_i_do_with_8xa800_cards/ | false | false | self | 1 | null |
What models are good for writing in the style of a certain author? | 1 | I'm wanting a model that i can feed transcripts of certain content i want to better imitate to inspire the stories i write.
something like
"in the style of 'joe pera talks with you,' and 'how to with john Wilson'" help me write a cohesive story that aims to breakdown and understand the theme of family traditions, with the accompanying broll of a man getting a haircut, a dog eating from the dinner table, and grandma cutting off the tops of chip bags."
Whats the best model i can download and essentially use a lora of their transcripts to craft stories that replicate their tone and humor style? | 2024-12-03T06:31:08 | https://www.reddit.com/r/LocalLLaMA/comments/1h5h94c/what_models_are_good_for_writing_in_the_style_of/ | SkyMartinezReddit | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5h94c | false | null | t3_1h5h94c | /r/LocalLLaMA/comments/1h5h94c/what_models_are_good_for_writing_in_the_style_of/ | false | false | self | 1 | null |
What can I do with multiple cards? | 1 | [removed] | 2024-12-03T06:31:30 | https://www.reddit.com/r/LocalLLaMA/comments/1h5h9bw/what_can_i_do_with_multiple_cards/ | CrazyShipTed | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5h9bw | false | null | t3_1h5h9bw | /r/LocalLLaMA/comments/1h5h9bw/what_can_i_do_with_multiple_cards/ | false | false | self | 1 | null |
Don't want to wast a 640GB server. | 1 | [removed] | 2024-12-03T06:35:22 | https://www.reddit.com/r/LocalLLaMA/comments/1h5hbg2/dont_want_to_wast_a_640gb_server/ | CrazyShipTed | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5hbg2 | false | null | t3_1h5hbg2 | /r/LocalLLaMA/comments/1h5hbg2/dont_want_to_wast_a_640gb_server/ | false | false | self | 1 | null |
Best way to build code summarizer app | 1 | [removed] | 2024-12-03T07:13:00 | https://www.reddit.com/r/LocalLLaMA/comments/1h5huxw/best_way_to_build_code_summarizer_app/ | RedOblivion01 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5huxw | false | null | t3_1h5huxw | /r/LocalLLaMA/comments/1h5huxw/best_way_to_build_code_summarizer_app/ | false | false | self | 1 | null |
I am noticing something not being taken into account in JP to EN Data sets | 1 | [removed] | 2024-12-03T07:35:44 | https://www.reddit.com/r/LocalLLaMA/comments/1h5i65c/i_am_noticing_something_not_being_taken_into/ | GTurkistane | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5i65c | false | null | t3_1h5i65c | /r/LocalLLaMA/comments/1h5i65c/i_am_noticing_something_not_being_taken_into/ | false | false | self | 1 | {'enabled': False, 'images': [{'id': 'dROJ8P7F4PhUWw6nsym9HkuS_crcn6Y_40Qk9nUOTrQ', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=108&crop=smart&auto=webp&s=5e126aab35df6f7a1cabaff2403ce2bf73eb0b25', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=216&crop=smart&auto=webp&s=517c479b1798541828fb521c85dd02943b705586', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=320&crop=smart&auto=webp&s=0e6d57056506f8ffd2547ffed80f93088ae8d060', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=640&crop=smart&auto=webp&s=31827c372f3fa6f36815da461afcffeb4d5990d3', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=960&crop=smart&auto=webp&s=553236c4b1663c341c287466062f8a14cd22977d', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?width=1080&crop=smart&auto=webp&s=658cf77a23c3c154327cc84b2021c0469495ac23', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/F0KXnjS-HXcQJqrn4h43l34xVTEI9nFbfhT0VpuMw2M.jpg?auto=webp&s=eaf6c5babc69df78263d3a2bff70dad1d779dac8', 'width': 1200}, 'variants': {}}]} |
Private Local LLM RAG (Advanced Pipelines) | 1 | [removed] | 2024-12-03T07:56:06 | https://www.reddit.com/r/LocalLLaMA/comments/1h5ig0x/private_local_llm_rag_advanced_pipelines/ | akhilpanja | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5ig0x | false | null | t3_1h5ig0x | /r/LocalLLaMA/comments/1h5ig0x/private_local_llm_rag_advanced_pipelines/ | false | false | self | 1 | null |
This is why uncensored model is important | 0 | 2024-12-03T07:58:53 | https://www.reddit.com/r/LocalLLaMA/comments/1h5ihav/this_is_why_uncensored_model_is_important/ | Internet--Traveller | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5ihav | false | null | t3_1h5ihav | /r/LocalLLaMA/comments/1h5ihav/this_is_why_uncensored_model_is_important/ | false | false | 0 | null |
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best tools for local translation (English ==> German) on a 3090 | 1 | [removed] | 2024-12-03T08:07:25 | https://www.reddit.com/r/LocalLLaMA/comments/1h5ilkk/best_tools_for_local_translation_english_german/ | llamahunter141 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5ilkk | false | null | t3_1h5ilkk | /r/LocalLLaMA/comments/1h5ilkk/best_tools_for_local_translation_english_german/ | false | false | self | 1 | null |
Assistance required for running LLMs locally | 1 | [removed] | 2024-12-03T08:07:28 | https://www.reddit.com/r/LocalLLaMA/comments/1h5illd/assistance_required_for_running_llms_locally/ | iamnotdeadnuts | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5illd | false | null | t3_1h5illd | /r/LocalLLaMA/comments/1h5illd/assistance_required_for_running_llms_locally/ | false | false | self | 1 | null |
I am noticing something not being taken into account in JP to EN Data sets | 1 | [removed] | 2024-12-03T08:17:33 | https://www.reddit.com/r/LocalLLaMA/comments/1h5iqiu/i_am_noticing_something_not_being_taken_into/ | Oehriehqkbt | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5iqiu | false | null | t3_1h5iqiu | /r/LocalLLaMA/comments/1h5iqiu/i_am_noticing_something_not_being_taken_into/ | false | false | self | 1 | null |
Ready-to-go open-source RAG implementations | 1 | [removed] | 2024-12-03T08:19:54 | https://www.reddit.com/r/LocalLLaMA/comments/1h5irmp/readytogo_opensource_rag_implementations/ | the_little_alex | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5irmp | false | null | t3_1h5irmp | /r/LocalLLaMA/comments/1h5irmp/readytogo_opensource_rag_implementations/ | false | false | self | 1 | null |
Ready-to-go open-source Retrieval-Augmented Generation implementations | 1 | [removed] | 2024-12-03T08:24:19 | https://www.reddit.com/r/LocalLLaMA/comments/1h5itsf/readytogo_opensource_retrievalaugmented/ | the_little_alex | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5itsf | false | null | t3_1h5itsf | /r/LocalLLaMA/comments/1h5itsf/readytogo_opensource_retrievalaugmented/ | false | false | self | 1 | null |
Hugging Face is doing a free and open course on fine tuning local LLMs!! | 1,061 | You will learn how to fine-tune, align, and use LLMs locally for your own use case.
This is a hands-on course designed to help you align language models for your unique needs. It’s beginner-friendly, with minimal requirements:
• Runs on most local machines
• Minimal GPU requirements
• No paid services needed
The course is based on the SmolLM2 series of models, but the skills you gain can be applied to larger models or other small language models. Perfect for getting started with model alignment without needing a supercomputer! 🚀
| 2024-12-03T09:38:26 | https://www.reddit.com/r/LocalLLaMA/comments/1h5js86/hugging_face_is_doing_a_free_and_open_course_on/ | bburtenshaw | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5js86 | false | null | t3_1h5js86 | /r/LocalLLaMA/comments/1h5js86/hugging_face_is_doing_a_free_and_open_course_on/ | false | false | self | 1,061 | {'enabled': False, 'images': [{'id': 'bqd3ulNb9tQv54vUmKW_1xKe9sMownzDzCiJtQ0GemA', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/ZgA7j-VJH_Zx8o-sQdG9StuoI15B1zqEDfswxmsJNxw.jpg?width=108&crop=smart&auto=webp&s=ca83cb8a3f43aa0e331627fa9c4e2f07a9b17f34', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/ZgA7j-VJH_Zx8o-sQdG9StuoI15B1zqEDfswxmsJNxw.jpg?width=216&crop=smart&auto=webp&s=269f7753595dcbadfb83f84b8ac1cbee9105dcf4', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/ZgA7j-VJH_Zx8o-sQdG9StuoI15B1zqEDfswxmsJNxw.jpg?width=320&crop=smart&auto=webp&s=94caf26051a7cce7816d7ecfede2dd264c7046ab', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/ZgA7j-VJH_Zx8o-sQdG9StuoI15B1zqEDfswxmsJNxw.jpg?width=640&crop=smart&auto=webp&s=e2491d06ce87351d7291b2d68d37a9e33de13e01', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/ZgA7j-VJH_Zx8o-sQdG9StuoI15B1zqEDfswxmsJNxw.jpg?width=960&crop=smart&auto=webp&s=e638337e125eeb3ef8f88ab3f57ed74c9366912b', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/ZgA7j-VJH_Zx8o-sQdG9StuoI15B1zqEDfswxmsJNxw.jpg?width=1080&crop=smart&auto=webp&s=08c9094e4bd392aee1bf4919bbb665ac77f8e89d', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/ZgA7j-VJH_Zx8o-sQdG9StuoI15B1zqEDfswxmsJNxw.jpg?auto=webp&s=3335aec872f697e24d1730621e86f70238ac78f8', 'width': 1200}, 'variants': {}}]} |
Inference for Embedding & Reranking Models on AMD
| 4 | Short Blog post on torch+rocm usage to run models on infinity, using a local docker setup. Nobody asked for it, but here it is: *running models using AMD using prebuilt docker image*. TIL that only 1 in every 100 users is on AMD, and a majority of deployments are on RTX30 and RTX40.
It fairly unknown to most people that AMD has decent PyTorch support for the MI250/300X series. The results on inference are on par with the one of the H100.
[https://huggingface.co/blog/michaelfeil/infinity-amd](https://huggingface.co/blog/michaelfeil/infinity-amd) | 2024-12-03T09:45:57 | https://www.reddit.com/r/LocalLLaMA/comments/1h5jvpx/inference_for_embedding_reranking_models_on_amd/ | OrganicMesh | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5jvpx | false | null | t3_1h5jvpx | /r/LocalLLaMA/comments/1h5jvpx/inference_for_embedding_reranking_models_on_amd/ | false | false | self | 4 | {'enabled': False, 'images': [{'id': 'x3a6ROR9KaRhVIyCZcNmZAf33xtuFS36IMfFr6NIbT8', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/1kRMQNvIN88Ud1BPq1eOao4U52-1TrY5VT-nX7VxzoU.jpg?width=108&crop=smart&auto=webp&s=215e274b77f8e1f4f9474f112a3d5aaf80039374', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/1kRMQNvIN88Ud1BPq1eOao4U52-1TrY5VT-nX7VxzoU.jpg?width=216&crop=smart&auto=webp&s=26d35ecb5e8857146016c6de0b50fe69fbaac03a', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/1kRMQNvIN88Ud1BPq1eOao4U52-1TrY5VT-nX7VxzoU.jpg?width=320&crop=smart&auto=webp&s=b4a69d8f794587f2aaf68e5565ea85efcb7b838e', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/1kRMQNvIN88Ud1BPq1eOao4U52-1TrY5VT-nX7VxzoU.jpg?width=640&crop=smart&auto=webp&s=674cdf072722344246de38fdbb5b8ea11098891c', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/1kRMQNvIN88Ud1BPq1eOao4U52-1TrY5VT-nX7VxzoU.jpg?width=960&crop=smart&auto=webp&s=7f5f61c6354f44340bf4d13da7940740970fb9f9', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/1kRMQNvIN88Ud1BPq1eOao4U52-1TrY5VT-nX7VxzoU.jpg?width=1080&crop=smart&auto=webp&s=7fa3db6c421799afeacc88813fbd88263abe8a9b', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/1kRMQNvIN88Ud1BPq1eOao4U52-1TrY5VT-nX7VxzoU.jpg?auto=webp&s=c01dd904b19012929729da51dcca0af7770c37fd', 'width': 1200}, 'variants': {}}]} |
Structured data chunking for RAG | 1 | [removed] | 2024-12-03T10:18:18 | https://www.reddit.com/r/LocalLLaMA/comments/1h5kbir/structured_data_chunking_for_rag/ | InternationalText292 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5kbir | false | null | t3_1h5kbir | /r/LocalLLaMA/comments/1h5kbir/structured_data_chunking_for_rag/ | false | false | self | 1 | null |
Generating prompts with uncensored LLM | 1 | [removed] | 2024-12-03T10:27:50 | https://www.reddit.com/r/LocalLLaMA/comments/1h5kg76/generating_prompts_with_uncensored_llm/ | aiwtl | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5kg76 | false | null | t3_1h5kg76 | /r/LocalLLaMA/comments/1h5kg76/generating_prompts_with_uncensored_llm/ | false | false | self | 1 | null |
Tencent releases Hunyuan-video, outperforms closed-source models like Gen3, Luma | 2 | [removed] | 2024-12-03T10:34:48 | https://www.reddit.com/r/LocalLLaMA/comments/1h5kjmy/tencent_releases_hunyuanvideo_outperforms/ | mehul_gupta1997 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5kjmy | false | null | t3_1h5kjmy | /r/LocalLLaMA/comments/1h5kjmy/tencent_releases_hunyuanvideo_outperforms/ | false | false | self | 2 | null |
Best local tool for querying a folder of documents? | 4 | I have used "chat with RTX" for this. I'm wondering what other tools are available for this. | 2024-12-03T10:56:53 | https://www.reddit.com/r/LocalLLaMA/comments/1h5kuub/best_local_tool_for_querying_a_folder_of_documents/ | Cunninghams_right | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5kuub | false | null | t3_1h5kuub | /r/LocalLLaMA/comments/1h5kuub/best_local_tool_for_querying_a_folder_of_documents/ | false | false | self | 4 | null |
Can anyone estimate what kind of hardware I would need to run Llama 3 400B with 32b? | 1 | [removed] | 2024-12-03T10:57:14 | https://www.reddit.com/r/LocalLLaMA/comments/1h5kv0z/can_anyone_estimate_what_kind_of_hardware_i_would/ | No_Goat_5701 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5kv0z | false | null | t3_1h5kv0z | /r/LocalLLaMA/comments/1h5kv0z/can_anyone_estimate_what_kind_of_hardware_i_would/ | false | false | self | 1 | null |
Small sized pretrained LLM model | 3 | hii does anyone have any idea of any small LLM (pre-trained models for 5-12 GB size .)
It should be able just to answer very basic stuff and that's about it. If so please share
thanks in advance :)) | 2024-12-03T11:19:02 | https://www.reddit.com/r/LocalLLaMA/comments/1h5l6ft/small_sized_pretrained_llm_model/ | Wide-Chef-7011 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1h5l6ft | false | null | t3_1h5l6ft | /r/LocalLLaMA/comments/1h5l6ft/small_sized_pretrained_llm_model/ | false | false | self | 3 | null |
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