title
stringlengths 1
300
| score
int64 0
8.54k
| selftext
stringlengths 0
40k
| created
timestamp[ns]date 2023-04-01 04:30:41
2025-06-30 03:16:29
⌀ | url
stringlengths 0
878
| author
stringlengths 3
20
| domain
stringlengths 0
82
| edited
timestamp[ns]date 1970-01-01 00:00:00
2025-06-26 17:30:18
| gilded
int64 0
2
| gildings
stringclasses 7
values | id
stringlengths 7
7
| locked
bool 2
classes | media
stringlengths 646
1.8k
⌀ | name
stringlengths 10
10
| permalink
stringlengths 33
82
| spoiler
bool 2
classes | stickied
bool 2
classes | thumbnail
stringlengths 4
213
| ups
int64 0
8.54k
| preview
stringlengths 301
5.01k
⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Lift Yourself | 1 | [removed] | 2025-01-16T22:51:23 | https://www.reddit.com/r/LocalLLaMA/comments/1i31qmy/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31qmy | false | null | t3_1i31qmy | /r/LocalLLaMA/comments/1i31qmy/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:51:41 | https://www.reddit.com/r/LocalLLaMA/comments/1i31quy/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31quy | false | null | t3_1i31quy | /r/LocalLLaMA/comments/1i31quy/lift_yourself/ | false | false | self | 1 | null |
Task queue app for multiple sessions / models / distributed runners | 6 | I would like to use a system where I can add multiple machines as model runners, e.g. one with a GPU for small models, and one with large memory but CPU only for larger models. Of course the CPU-only model will be super-slow, but the point is it will be much better. When I submit a task, it could schedule it for each model, and put it in their respective queue. The machines would pull these task and burn through them as they can, submitting the results. The UI would collect these and present them as they become available.
Is there any software that does it? | 2025-01-16T22:51:53 | https://www.reddit.com/r/LocalLLaMA/comments/1i31r0k/task_queue_app_for_multiple_sessions_models/ | yelling-at-clouds-40 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31r0k | false | null | t3_1i31r0k | /r/LocalLLaMA/comments/1i31r0k/task_queue_app_for_multiple_sessions_models/ | false | false | self | 6 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:51:57 | https://www.reddit.com/r/LocalLLaMA/comments/1i31r24/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31r24 | false | null | t3_1i31r24 | /r/LocalLLaMA/comments/1i31r24/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:52:12 | https://www.reddit.com/r/LocalLLaMA/comments/1i31r99/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31r99 | false | null | t3_1i31r99 | /r/LocalLLaMA/comments/1i31r99/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:52:29 | https://www.reddit.com/r/LocalLLaMA/comments/1i31rhw/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31rhw | false | null | t3_1i31rhw | /r/LocalLLaMA/comments/1i31rhw/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:52:44 | https://www.reddit.com/r/LocalLLaMA/comments/1i31roz/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31roz | false | null | t3_1i31roz | /r/LocalLLaMA/comments/1i31roz/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:52:59 | https://www.reddit.com/r/LocalLLaMA/comments/1i31rwk/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31rwk | false | null | t3_1i31rwk | /r/LocalLLaMA/comments/1i31rwk/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:53:16 | https://www.reddit.com/r/LocalLLaMA/comments/1i31s4b/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31s4b | false | null | t3_1i31s4b | /r/LocalLLaMA/comments/1i31s4b/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:53:31 | https://www.reddit.com/r/LocalLLaMA/comments/1i31sb5/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31sb5 | false | null | t3_1i31sb5 | /r/LocalLLaMA/comments/1i31sb5/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:53:47 | https://www.reddit.com/r/LocalLLaMA/comments/1i31siw/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31siw | false | null | t3_1i31siw | /r/LocalLLaMA/comments/1i31siw/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:54:02 | https://www.reddit.com/r/LocalLLaMA/comments/1i31sqd/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31sqd | false | null | t3_1i31sqd | /r/LocalLLaMA/comments/1i31sqd/lift_yourself/ | false | false | self | 1 | null |
How to use chat templates for multicharacter roleplays? | 9 | I have implemented my own roleplay front-end for KoboldCpp. In contrast to SillyTavern and BackyardAI, my approach is not character-centric but rather scenario-centric. Both AI and the user can control multiple characters, and AI makes its own choice of who should speak next.
At first, I did not even bother to figure out how to use chat templates. I just send a simple example dialogue to the LLM together with my scenario:
Bob: Hi!
Anna: Hello!
Then I launch the generation and poll the API to check for the result. I look for a valid \`Character Name:\` marker in the response and allow only the characters that are setup for AI control. If I receive one more character marker, I stop the generation to avoid the infamous "speaking for others" issue, and clean up the response to remove the unnecessary text.
I'm testing it now and even Llama 3.2 3B seems to work quite OK with this setup.
However, I've heard that some models benefit from system prompts, and, as I understand, to pass the system prompt to the model, I need to use a proper chat template for the specific model.
And now we come to the root of the problem. **Chat templates seem to be centered on the idea of only two parties - the user and the assistant. I have more parties. How would I encode their messages in a chat template?**
A naive approach would be to send the system prompt with the proper formatting for the template, and then just dump the entire accumulated context with the scenario, character descriptions and all the chat messages into a single "assistant" message and ignore the user part of the template completely.
But wouldn't this somehow make the model less smart and not obey the scenario as well as it would if I separate the chat messages and create a single assistant (or user) message for every character's reply?
What are the practical effects of the chat template on the inference quality? Is the chat template just a convenient wrapper to properly separate messages in more complex situations or does it actually improve the model's behavior? | 2025-01-16T22:54:17 | https://www.reddit.com/r/LocalLLaMA/comments/1i31sxj/how_to_use_chat_templates_for_multicharacter/ | martinerous | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31sxj | false | null | t3_1i31sxj | /r/LocalLLaMA/comments/1i31sxj/how_to_use_chat_templates_for_multicharacter/ | false | false | self | 9 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:54:18 | https://www.reddit.com/r/LocalLLaMA/comments/1i31sxs/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31sxs | false | null | t3_1i31sxs | /r/LocalLLaMA/comments/1i31sxs/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:54:34 | https://www.reddit.com/r/LocalLLaMA/comments/1i31t57/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31t57 | false | null | t3_1i31t57 | /r/LocalLLaMA/comments/1i31t57/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:54:49 | https://www.reddit.com/r/LocalLLaMA/comments/1i31tc3/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31tc3 | false | null | t3_1i31tc3 | /r/LocalLLaMA/comments/1i31tc3/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:55:05 | https://www.reddit.com/r/LocalLLaMA/comments/1i31tiy/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31tiy | false | null | t3_1i31tiy | /r/LocalLLaMA/comments/1i31tiy/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:55:21 | https://www.reddit.com/r/LocalLLaMA/comments/1i31tpz/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31tpz | false | null | t3_1i31tpz | /r/LocalLLaMA/comments/1i31tpz/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:55:37 | https://www.reddit.com/r/LocalLLaMA/comments/1i31twl/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31twl | false | null | t3_1i31twl | /r/LocalLLaMA/comments/1i31twl/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:55:52 | https://www.reddit.com/r/LocalLLaMA/comments/1i31u4j/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31u4j | false | null | t3_1i31u4j | /r/LocalLLaMA/comments/1i31u4j/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:56:08 | https://www.reddit.com/r/LocalLLaMA/comments/1i31ubm/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31ubm | false | null | t3_1i31ubm | /r/LocalLLaMA/comments/1i31ubm/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:56:24 | https://www.reddit.com/r/LocalLLaMA/comments/1i31uid/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31uid | false | null | t3_1i31uid | /r/LocalLLaMA/comments/1i31uid/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:56:40 | https://www.reddit.com/r/LocalLLaMA/comments/1i31uqg/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31uqg | false | null | t3_1i31uqg | /r/LocalLLaMA/comments/1i31uqg/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:56:56 | https://www.reddit.com/r/LocalLLaMA/comments/1i31uyc/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31uyc | false | null | t3_1i31uyc | /r/LocalLLaMA/comments/1i31uyc/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:57:11 | https://www.reddit.com/r/LocalLLaMA/comments/1i31v55/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31v55 | false | null | t3_1i31v55 | /r/LocalLLaMA/comments/1i31v55/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:57:27 | https://www.reddit.com/r/LocalLLaMA/comments/1i31vcs/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31vcs | false | null | t3_1i31vcs | /r/LocalLLaMA/comments/1i31vcs/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:57:42 | https://www.reddit.com/r/LocalLLaMA/comments/1i31vk6/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31vk6 | false | null | t3_1i31vk6 | /r/LocalLLaMA/comments/1i31vk6/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:57:59 | https://www.reddit.com/r/LocalLLaMA/comments/1i31vqz/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31vqz | false | null | t3_1i31vqz | /r/LocalLLaMA/comments/1i31vqz/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:58:14 | https://www.reddit.com/r/LocalLLaMA/comments/1i31vye/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31vye | false | null | t3_1i31vye | /r/LocalLLaMA/comments/1i31vye/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:58:30 | https://www.reddit.com/r/LocalLLaMA/comments/1i31w62/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31w62 | false | null | t3_1i31w62 | /r/LocalLLaMA/comments/1i31w62/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T22:58:45 | https://www.reddit.com/r/LocalLLaMA/comments/1i31wd0/lift_yourself/ | UpsetApplication9345 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31wd0 | false | null | t3_1i31wd0 | /r/LocalLLaMA/comments/1i31wd0/lift_yourself/ | false | false | self | 1 | null |
Lift Yourself | 1 | [removed] | 2025-01-16T23:03:09 | https://www.reddit.com/r/LocalLLaMA/comments/1i31zwc/lift_yourself/ | maniac-maniac-8493 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i31zwc | false | null | t3_1i31zwc | /r/LocalLLaMA/comments/1i31zwc/lift_yourself/ | false | false | self | 1 | null |
basic shit | 1 | [removed] | 2025-01-16T23:06:33 | https://www.reddit.com/r/LocalLLaMA/comments/1i322je/basic_shit/ | input_output_stream3 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i322je | false | null | t3_1i322je | /r/LocalLLaMA/comments/1i322je/basic_shit/ | false | false | self | 1 | null |
Why tools like Perplexity can't accurately give me custom percentages? | 1 | [removed] | 2025-01-16T23:59:52 | https://www.reddit.com/r/LocalLLaMA/comments/1i3377x/why_tools_like_perplexity_cant_accurately_give_me/ | vamos-viendo | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3377x | false | null | t3_1i3377x | /r/LocalLLaMA/comments/1i3377x/why_tools_like_perplexity_cant_accurately_give_me/ | false | false | self | 1 | null |
Agentic AI learning resources | 1 | Looking for resources to learn how to use agentic ai to automate workflows. | 2025-01-17T00:18:29 | https://www.reddit.com/r/LocalLLaMA/comments/1i33lea/agentic_ai_learning_resources/ | akbfs826 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i33lea | false | null | t3_1i33lea | /r/LocalLLaMA/comments/1i33lea/agentic_ai_learning_resources/ | false | false | self | 1 | null |
GPU Enclosure Experiences? | 3 | Sorry for the noob question, but will an eGPU enclosure work as well for LLM loading as it would for gaming?
I have a 4070ti incompatible with my PC (OEM XPS PSU can’t handle it). The card I have now is a 3060Ti. I got the 4070 so cheap that even with an enclosure it’d be less than avg used price.
If anyone has good/bad eGPU experience, that might sway me on keeping vs selling. It’s just been sitting in the box for awhile. | 2025-01-17T00:39:15 | https://www.reddit.com/r/LocalLLaMA/comments/1i340rd/gpu_enclosure_experiences/ | ilovepolthavemybabie | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i340rd | false | null | t3_1i340rd | /r/LocalLLaMA/comments/1i340rd/gpu_enclosure_experiences/ | false | false | self | 3 | null |
Why do tools like Perplexity struggle to calculate accurate stats from different sources when the exact number is not posted online? | 1 | I’ve been wondering why tools like Perplexity seem to fall short on calculating stats that don’t already exist online. Perplexity tries—with its reasoning steps—but the results often fail in accuracy or iterative depth.
For example:
* **“What percentage of countries with universal healthcare also have female leaders?”**
If this functionality exists, I haven’t seen it work well. Curious—what do you think is the blocker here?
* Is it a complexity or cost issue (the multi-step iterative reasoning)?
* Is the demand just not there?
* Are these tools just focusing elsewhere? | 2025-01-17T00:46:39 | https://www.reddit.com/r/LocalLLaMA/comments/1i34642/why_do_tools_like_perplexity_struggle_to/ | vamos-viendo | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i34642 | false | null | t3_1i34642 | /r/LocalLLaMA/comments/1i34642/why_do_tools_like_perplexity_struggle_to/ | false | false | self | 1 | null |
4x AMD Instinct AI Server + Mistral 7B + vLLM | 25 | 2025-01-17T01:38:35 | https://v.redd.it/1sni53vckgde1 | Any_Praline_8178 | /r/LocalLLaMA/comments/1i357ov/4x_amd_instinct_ai_server_mistral_7b_vllm/ | 1970-01-01T00:00:00 | 0 | {} | 1i357ov | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/1sni53vckgde1/DASHPlaylist.mpd?a=1739799518%2CNjQ3ZWExYWRhODk1OTMyNWFmZDViYjUwMWFiMTJhZTg2MGIwZGM5YjI5ZGE3NzI3M2EyODUyM2VkODAyYmQxMQ%3D%3D&v=1&f=sd', 'duration': 14, 'fallback_url': 'https://v.redd.it/1sni53vckgde1/DASH_1080.mp4?source=fallback', 'has_audio': False, 'height': 1904, 'hls_url': 'https://v.redd.it/1sni53vckgde1/HLSPlaylist.m3u8?a=1739799518%2COWQyZGRjOWYxYzZjOTExNmI5OWJjMDg4N2FlOWE3NTI5MmRmNmFhZDUyYTJjYzZiMzRhNTE2NzMxNjQ4OGQxNw%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/1sni53vckgde1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1080}} | t3_1i357ov | /r/LocalLLaMA/comments/1i357ov/4x_amd_instinct_ai_server_mistral_7b_vllm/ | false | false | 25 | {'enabled': False, 'images': [{'id': 'OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ', 'resolutions': [{'height': 190, 'url': 'https://external-preview.redd.it/OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ.png?width=108&crop=smart&format=pjpg&auto=webp&s=f73d86812aa437d36cfaa456f9c268c14f7de010', 'width': 108}, {'height': 380, 'url': 'https://external-preview.redd.it/OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ.png?width=216&crop=smart&format=pjpg&auto=webp&s=857a8a96e5fff18d161d7695bdd103bbfab317a2', 'width': 216}, {'height': 563, 'url': 'https://external-preview.redd.it/OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ.png?width=320&crop=smart&format=pjpg&auto=webp&s=e243718680aec27b48672482bc873ab0c6072a3e', 'width': 320}, {'height': 1127, 'url': 'https://external-preview.redd.it/OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ.png?width=640&crop=smart&format=pjpg&auto=webp&s=9183be6e05dd063f150fee5a4e6f168acc5b8150', 'width': 640}, {'height': 1691, 'url': 'https://external-preview.redd.it/OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ.png?width=960&crop=smart&format=pjpg&auto=webp&s=a2740feff2e21151ede7bc5d6ab9aaa1b61ab5af', 'width': 960}, {'height': 1903, 'url': 'https://external-preview.redd.it/OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ.png?width=1080&crop=smart&format=pjpg&auto=webp&s=59c866cd6cb65f2836c1e0b508fb0a82814217fc', 'width': 1080}], 'source': {'height': 3796, 'url': 'https://external-preview.redd.it/OXZzbzY0dmNrZ2RlMYrnczNrVsQkdH3BrjnNDBSvBen7AmAirsnxCxjuWUYQ.png?format=pjpg&auto=webp&s=67ab0e6a91bd668383954b545cc0e6d37ec5d73c', 'width': 2154}, 'variants': {}}]} |
||
My Tesla P40 just caught on fire and exploded… help? | 41 | https://imgur.com/a/1ViaFVL
Um… so, this GPU has an insanely long lore. To summarize, I ended up trying to sell it, UPS ravaged the box and the buyer claimed the GPU didn’t work anymore (wouldn’t power on), I received it back, tried to power it up, and it immediately caught on fire in catastrophic fashion and shot flames into my motherboard.
I’m powering them with a good quality PCIe to EPS adapter, which I just used again to try and check if it was indeed dead. Well, it sure as hell is now.
Uh, what the hell happened? What is the component that exploded? It looks to be power related and it had a thermal pad on the backplate that is now scorched.
I actually have ANOTHER P40 from this shipment that I’m wanting to test and I’m absolutely mortified to plug it in now. I don’t think I’ll ever trust a PC build again. | 2025-01-17T01:52:52 | https://www.reddit.com/r/LocalLLaMA/comments/1i35hs3/my_tesla_p40_just_caught_on_fire_and_exploded_help/ | Cressio | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i35hs3 | false | null | t3_1i35hs3 | /r/LocalLLaMA/comments/1i35hs3/my_tesla_p40_just_caught_on_fire_and_exploded_help/ | false | false | self | 41 | {'enabled': False, 'images': [{'id': 'E-rEcp6PSN_oBerqUpkWMIoOoZCxhsfAvK9QjqHW9fg', 'resolutions': [{'height': 144, 'url': 'https://external-preview.redd.it/vZr1Jnu6NQVJE51kTm7VDDk2w5Zew4osUGQoixqN5w4.jpg?width=108&crop=smart&auto=webp&s=6406f4edaf63b470986facd965bce9eceb1b77d1', 'width': 108}, {'height': 288, 'url': 'https://external-preview.redd.it/vZr1Jnu6NQVJE51kTm7VDDk2w5Zew4osUGQoixqN5w4.jpg?width=216&crop=smart&auto=webp&s=d3d880d0bfee2ef36d90ed4411bb14c0afd5fdb9', 'width': 216}, {'height': 426, 'url': 'https://external-preview.redd.it/vZr1Jnu6NQVJE51kTm7VDDk2w5Zew4osUGQoixqN5w4.jpg?width=320&crop=smart&auto=webp&s=69d11bc570e4a139e657d3164ec051dfcc1a289c', 'width': 320}, {'height': 853, 'url': 'https://external-preview.redd.it/vZr1Jnu6NQVJE51kTm7VDDk2w5Zew4osUGQoixqN5w4.jpg?width=640&crop=smart&auto=webp&s=c0a1884c9ec4bb671379b78dae5b80075c11f8ac', 'width': 640}, {'height': 1280, 'url': 'https://external-preview.redd.it/vZr1Jnu6NQVJE51kTm7VDDk2w5Zew4osUGQoixqN5w4.jpg?width=960&crop=smart&auto=webp&s=0202b0dff005e4cd5eda82101eeced422cc34783', 'width': 960}, {'height': 1440, 'url': 'https://external-preview.redd.it/vZr1Jnu6NQVJE51kTm7VDDk2w5Zew4osUGQoixqN5w4.jpg?width=1080&crop=smart&auto=webp&s=7e7eefffaaefb2994066c49f745ef39fcf442d63', 'width': 1080}], 'source': {'height': 2048, 'url': 'https://external-preview.redd.it/vZr1Jnu6NQVJE51kTm7VDDk2w5Zew4osUGQoixqN5w4.jpg?auto=webp&s=ec856041a9243ecc48066b868020726a16dc796d', 'width': 1536}, 'variants': {}}]} |
I made a simple python scripts that automate deletion of your ChatGPT chats | 4 | Hey! I was considering whether to post this or not, and I decided other people may have had this issue too, where you been using chatGPT all the time, there's like a thousand chats, I was in this predicament and made a program that I made on Linux for firefox with Selenium, that essentially automatically goes through and starts deleting your chats on chatGPT.
I made it on Linux, I have no clue the compatibility with windows, and it's for firefox, If anyone else who's in this predicament wants to use it feel free!
Github:
[https://github.com/TheBlewish/Automated-ChatGPT-Chats-Deletion](https://github.com/TheBlewish/Automated-ChatGPT-Chats-Deletion) | 2025-01-17T01:55:46 | https://www.reddit.com/r/LocalLLaMA/comments/1i35juw/i_made_a_simple_python_scripts_that_automate/ | CuriousAustralianBoy | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i35juw | false | null | t3_1i35juw | /r/LocalLLaMA/comments/1i35juw/i_made_a_simple_python_scripts_that_automate/ | false | false | self | 4 | {'enabled': False, 'images': [{'id': 'cj4NLfAcHSFNnZHO3wBhBMHs9hZrA788h5V_5y0EhR4', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/WbfKxUiFHUZWwPakKfgmxYEQK-VyAFhFz7iECKT71Ts.jpg?width=108&crop=smart&auto=webp&s=f710ffdeb1dd3c038f8ab5f6485626429190537e', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/WbfKxUiFHUZWwPakKfgmxYEQK-VyAFhFz7iECKT71Ts.jpg?width=216&crop=smart&auto=webp&s=a19d057972441f10ac83a504f67cd2eb8994e2d5', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/WbfKxUiFHUZWwPakKfgmxYEQK-VyAFhFz7iECKT71Ts.jpg?width=320&crop=smart&auto=webp&s=73cacdef58916043e1243b20ef272a78967b1025', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/WbfKxUiFHUZWwPakKfgmxYEQK-VyAFhFz7iECKT71Ts.jpg?width=640&crop=smart&auto=webp&s=fea84ec245b1846bbef07b78b6f851ae62ba7d20', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/WbfKxUiFHUZWwPakKfgmxYEQK-VyAFhFz7iECKT71Ts.jpg?width=960&crop=smart&auto=webp&s=48e0e1f42881c449aef62cb68a857b57e161ba84', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/WbfKxUiFHUZWwPakKfgmxYEQK-VyAFhFz7iECKT71Ts.jpg?width=1080&crop=smart&auto=webp&s=c07155c7cb8168bc4c8d90fc6d852e3725493c04', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/WbfKxUiFHUZWwPakKfgmxYEQK-VyAFhFz7iECKT71Ts.jpg?auto=webp&s=a23467b1ca67f20bea327db739156bcc4ba003b0', 'width': 1200}, 'variants': {}}]} |
You are an absolute moron for believing in the hype of “AI Agents”. | 1 | 2025-01-17T02:11:41 | https://medium.com/p/c0f760e7e48e | No-Definition-2886 | medium.com | 1970-01-01T00:00:00 | 0 | {} | 1i35uvy | false | null | t3_1i35uvy | /r/LocalLLaMA/comments/1i35uvy/you_are_an_absolute_moron_for_believing_in_the/ | false | false | 1 | {'enabled': False, 'images': [{'id': '1E3xxo6_PV-k6mv0objYiPTFRGYWWtCzOdyf3J7s5os', 'resolutions': [{'height': 81, 'url': 'https://external-preview.redd.it/MoVplprQIrTO-LgxJ2svkt9m4t3YwydFjrCCUTlQwHs.jpg?width=108&crop=smart&auto=webp&s=334518867597e354884e8b54e5cf83921bcded5c', 'width': 108}, {'height': 162, 'url': 'https://external-preview.redd.it/MoVplprQIrTO-LgxJ2svkt9m4t3YwydFjrCCUTlQwHs.jpg?width=216&crop=smart&auto=webp&s=6d625a7ddb8d5c851d5f0b76fc624c9582b33aa3', 'width': 216}, {'height': 240, 'url': 'https://external-preview.redd.it/MoVplprQIrTO-LgxJ2svkt9m4t3YwydFjrCCUTlQwHs.jpg?width=320&crop=smart&auto=webp&s=2c8919aad1685b42a30cc4aec06ced79fb89224f', 'width': 320}, {'height': 480, 'url': 'https://external-preview.redd.it/MoVplprQIrTO-LgxJ2svkt9m4t3YwydFjrCCUTlQwHs.jpg?width=640&crop=smart&auto=webp&s=2690d395ac52feed727c51785ec54f2ff6ed439d', 'width': 640}, {'height': 720, 'url': 'https://external-preview.redd.it/MoVplprQIrTO-LgxJ2svkt9m4t3YwydFjrCCUTlQwHs.jpg?width=960&crop=smart&auto=webp&s=5b4f0a3df6b38e4c3c7d919359f108a2d2ca8474', 'width': 960}], 'source': {'height': 768, 'url': 'https://external-preview.redd.it/MoVplprQIrTO-LgxJ2svkt9m4t3YwydFjrCCUTlQwHs.jpg?auto=webp&s=e9e71292923dd0cb2bb95d0ea47d3de1dbf01216', 'width': 1024}, 'variants': {}}]} |
||
Ollama on 16GB Ram | 1 | [removed] | 2025-01-17T02:31:54 | https://www.reddit.com/r/LocalLLaMA/comments/1i3693h/ollama_on_16gb_ram/ | TimelySentence2063 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3693h | false | null | t3_1i3693h | /r/LocalLLaMA/comments/1i3693h/ollama_on_16gb_ram/ | false | false | self | 1 | null |
Deepseek V3 running on my local dual CPU PC, 384GB RAM, no GPU! | 1 | 2025-01-17T03:07:21 | https://v.redd.it/gexlt6mb0hde1 | Big_Specific9749 | v.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1i36wz8 | false | {'reddit_video': {'bitrate_kbps': 5000, 'dash_url': 'https://v.redd.it/gexlt6mb0hde1/DASHPlaylist.mpd?a=1739675255%2CN2FjMTU5ZDZjNTUyM2JmNjFlY2MyZWEwMzQ0ZDMxZjQ1Y2JmOTRiYTgzMGE3MDlhZTQ3OWRiMWJhMGNiZDc4MA%3D%3D&v=1&f=sd', 'duration': 64, 'fallback_url': 'https://v.redd.it/gexlt6mb0hde1/DASH_1080.mp4?source=fallback', 'has_audio': False, 'height': 1120, 'hls_url': 'https://v.redd.it/gexlt6mb0hde1/HLSPlaylist.m3u8?a=1739675255%2CY2RiOWNmODJlN2Q4M2ZkNjQ2OTMyZTEwZWNkZTk5YzJjNWVhMTk1MmEzNTRiZDg2YjY0YjQ2ODk3ODA4ZGJiZA%3D%3D&v=1&f=sd', 'is_gif': False, 'scrubber_media_url': 'https://v.redd.it/gexlt6mb0hde1/DASH_96.mp4', 'transcoding_status': 'completed', 'width': 1080}} | t3_1i36wz8 | /r/LocalLLaMA/comments/1i36wz8/deepseek_v3_running_on_my_local_dual_cpu_pc_384gb/ | false | false | 1 | {'enabled': False, 'images': [{'id': 'MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a', 'resolutions': [{'height': 111, 'url': 'https://external-preview.redd.it/MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a.png?width=108&crop=smart&format=pjpg&auto=webp&s=606873d933cd9090c81f286465b9e59976e07539', 'width': 108}, {'height': 223, 'url': 'https://external-preview.redd.it/MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a.png?width=216&crop=smart&format=pjpg&auto=webp&s=73eacf77341316911f6dc53b880d4081066f8aab', 'width': 216}, {'height': 331, 'url': 'https://external-preview.redd.it/MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a.png?width=320&crop=smart&format=pjpg&auto=webp&s=9a369cfe887819865e417f56785e20fe89961de1', 'width': 320}, {'height': 663, 'url': 'https://external-preview.redd.it/MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a.png?width=640&crop=smart&format=pjpg&auto=webp&s=87a234bd1b8cd9e398957a22d32a7a875db14737', 'width': 640}, {'height': 995, 'url': 'https://external-preview.redd.it/MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a.png?width=960&crop=smart&format=pjpg&auto=webp&s=0cfe622e0fdb30f13c759797c08594de2e74dde8', 'width': 960}, {'height': 1119, 'url': 'https://external-preview.redd.it/MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a.png?width=1080&crop=smart&format=pjpg&auto=webp&s=bed0d843b952c4b45f281e9b0ec69a94ce5f8ea6', 'width': 1080}], 'source': {'height': 2152, 'url': 'https://external-preview.redd.it/MGhvZHZ2amIwaGRlMe1V2s-JyylPqB0ZjZe_rqNYTsy1A_T8uoIGo2wBts3a.png?format=pjpg&auto=webp&s=b2a42bfcc1acee16b06f023164a6eaac53cdbff9', 'width': 2076}, 'variants': {}}]} |
||
Whats the current State-of-The-Art for voice cloning? | 12 | last time i checked which was quite a while voice cloning and like making AI song covers and etc used RVC v2 but im sure a LOT has changed since then Ive heard a lot of stuff about tts models like the new 82M model but i dont think ive heard specifically about voice cloning and cover tools | 2025-01-17T04:02:10 | https://www.reddit.com/r/LocalLLaMA/comments/1i37x87/whats_the_current_stateoftheart_for_voice_cloning/ | pigeon57434 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i37x87 | false | null | t3_1i37x87 | /r/LocalLLaMA/comments/1i37x87/whats_the_current_stateoftheart_for_voice_cloning/ | false | false | self | 12 | null |
What is your stage rn? | 0 | 2025-01-17T04:09:43 | iamnotdeadnuts | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1i381za | false | null | t3_1i381za | /r/LocalLLaMA/comments/1i381za/what_is_your_stage_rn/ | false | false | 0 | {'enabled': True, 'images': [{'id': 'XECOeI3ffVexM6nF7rgjvy0TQnhpCbibT-WsMBDTqFw', 'resolutions': [{'height': 95, 'url': 'https://preview.redd.it/u9zca70gbhde1.png?width=108&crop=smart&auto=webp&s=0d7c9f64fdcd1a5847d2effaafdb021d04cc642e', 'width': 108}, {'height': 190, 'url': 'https://preview.redd.it/u9zca70gbhde1.png?width=216&crop=smart&auto=webp&s=b6648f302b941824b617cae5fdb8339e01bd1db5', 'width': 216}, {'height': 282, 'url': 'https://preview.redd.it/u9zca70gbhde1.png?width=320&crop=smart&auto=webp&s=82da4657160e701edc541b96d4e3ec0be53858ba', 'width': 320}, {'height': 564, 'url': 'https://preview.redd.it/u9zca70gbhde1.png?width=640&crop=smart&auto=webp&s=5afe2198ee43f27a23f3b504625eef2a3ba63184', 'width': 640}], 'source': {'height': 762, 'url': 'https://preview.redd.it/u9zca70gbhde1.png?auto=webp&s=f13e9bf753dba68bcc595fe73ea9cc3ea3013638', 'width': 864}, 'variants': {}}]} |
|||
Running Kokoro-82M ONNX TTS Model in the Browser | 1 | [removed] | 2025-01-17T04:13:25 | https://www.reddit.com/r/LocalLLaMA/comments/1i3848r/running_kokoro82m_onnx_tts_model_in_the_browser/ | BluebirdInfinite1812 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3848r | false | null | t3_1i3848r | /r/LocalLLaMA/comments/1i3848r/running_kokoro82m_onnx_tts_model_in_the_browser/ | false | false | nsfw | 1 | null |
Titan architecture and reasoning | 7 | So I've been thinking about how all the commercial models have been focusing on creating a better reasoning model with quite possibly incorporating CoT into the training process and scaling it out.
And with the release of the Titans architecture where it retains "selective long term memory" I wonder if this architecture can better learn the important reasoning steps found in CoT process and thus actually be able to be a model that very closely and very successfully mimics a reasoning AI. If that's the case, with 2M+ context and long-term memory in the model itself, will we possibly see an AI that potentially could behave very much like AGI like we have imagined AI would be? | 2025-01-17T04:18:21 | https://www.reddit.com/r/LocalLLaMA/comments/1i38790/titan_architecture_and_reasoning/ | hugganao | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i38790 | false | null | t3_1i38790 | /r/LocalLLaMA/comments/1i38790/titan_architecture_and_reasoning/ | false | false | self | 7 | null |
Avoid risky dependencies in AI-generated code with Opensource Project CodeGate | 0 | 2025-01-17T04:19:03 | https://www.youtube.com/watch?v=WimBevc_Ji0 | zero_proof_fork | youtube.com | 1970-01-01T00:00:00 | 0 | {} | 1i387pt | false | {'oembed': {'author_name': 'Stacklok', 'author_url': 'https://www.youtube.com/@Stacklok', 'height': 200, 'html': '<iframe width="356" height="200" src="https://www.youtube.com/embed/WimBevc_Ji0?feature=oembed&enablejsapi=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen title="Avoid risky dependencies in AI-generated code with CodeGate"></iframe>', 'provider_name': 'YouTube', 'provider_url': 'https://www.youtube.com/', 'thumbnail_height': 360, 'thumbnail_url': 'https://i.ytimg.com/vi/WimBevc_Ji0/hqdefault.jpg', 'thumbnail_width': 480, 'title': 'Avoid risky dependencies in AI-generated code with CodeGate', 'type': 'video', 'version': '1.0', 'width': 356}, 'type': 'youtube.com'} | t3_1i387pt | /r/LocalLLaMA/comments/1i387pt/avoid_risky_dependencies_in_aigenerated_code_with/ | false | false | 0 | {'enabled': False, 'images': [{'id': '5aILawYwqbWLyzZjfiomKvNrcaZRH6vtzlj4qSCPjbY', 'resolutions': [{'height': 81, 'url': 'https://external-preview.redd.it/OkXGejKiKrfg4RPA1jsrMlEJ821qsUeqhVRM09e9r0E.jpg?width=108&crop=smart&auto=webp&s=a75e88847b164d8d7e208c59131a5d06be7dc029', 'width': 108}, {'height': 162, 'url': 'https://external-preview.redd.it/OkXGejKiKrfg4RPA1jsrMlEJ821qsUeqhVRM09e9r0E.jpg?width=216&crop=smart&auto=webp&s=b7872fd067a63e1234f360b0f413834ac99edef6', 'width': 216}, {'height': 240, 'url': 'https://external-preview.redd.it/OkXGejKiKrfg4RPA1jsrMlEJ821qsUeqhVRM09e9r0E.jpg?width=320&crop=smart&auto=webp&s=74b7723061a361dd09162041dab7e39b05b193c5', 'width': 320}], 'source': {'height': 360, 'url': 'https://external-preview.redd.it/OkXGejKiKrfg4RPA1jsrMlEJ821qsUeqhVRM09e9r0E.jpg?auto=webp&s=1a32ff9d457a40ad5772e188008243930649a318', 'width': 480}, 'variants': {}}]} |
||
Running Kokoro-82M ONNX TTS Model in the Browser
| 1 | [removed] | 2025-01-17T04:28:17 | https://www.reddit.com/r/LocalLLaMA/comments/1i38dfv/running_kokoro82m_onnx_tts_model_in_the_browser/ | BluebirdInfinite1812 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i38dfv | false | null | t3_1i38dfv | /r/LocalLLaMA/comments/1i38dfv/running_kokoro82m_onnx_tts_model_in_the_browser/ | false | false | self | 1 | null |
Which do you think will be better: Qwen-3 or Llama-4 | 1 | and which do you think will come out first? and more importantly will llama-4 actually have a middle ground size between 8 and 70 so i can run it | 2025-01-17T04:37:46 | https://www.reddit.com/r/LocalLLaMA/comments/1i38jih/which_do_you_think_will_be_better_qwen3_or_llama4/ | pigeon57434 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i38jih | false | null | t3_1i38jih | /r/LocalLLaMA/comments/1i38jih/which_do_you_think_will_be_better_qwen3_or_llama4/ | false | false | self | 1 | null |
Vision Models for extracting Attributes
| 1 | [removed] | 2025-01-17T04:38:22 | https://www.reddit.com/r/LocalLLaMA/comments/1i38jvd/vision_models_for_extracting_attributes/ | Potential_Nature4974 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i38jvd | false | null | t3_1i38jvd | /r/LocalLLaMA/comments/1i38jvd/vision_models_for_extracting_attributes/ | false | false | self | 1 | null |
Here's what I've found for those of you comparing mistral codestral 25.01 against claude 3.5 sonnet. | 0 | Mistral's new Codestral 25.01 is impressive on paper (support for over 80 coding languages!), so I compared it with other leading models like Claude 3.5 Sonnet to see how they stack up for coding tasks.
* Performance Metrics: Codestral achieves an impressive HumanEval score of 86.6%, while Claude stands strong with competitive scores in various programming languages.
* Speed: Codestral claims to generate code twice as fast as its predecessor, which could be a game-changer for developers needing rapid assistance.
* Language Support: Supporting over 80 languages gives Codestral a versatility edge; however, Claude also offers robust support across popular languages.
* Context Length: With a context length of 256k tokens, Codestral may handle larger codebases better than Claude's 200k limit.
Both models have their strengths and weaknesses. From my tests, I still think Claude is better overall. But, what are your thoughts on their performance in practical applications? Btw, I found this detailed article that compares codestral 25.01 with other models like Claude, GPT, DeepSeek etc.: [https://blog.getbind.co/2025/01/15/mistral-codestral-25-01-is-it-the-best-model-for-coding/](https://blog.getbind.co/2025/01/15/mistral-codestral-25-01-is-it-the-best-model-for-coding/)
| 2025-01-17T04:42:06 | https://www.reddit.com/r/LocalLLaMA/comments/1i38m86/heres_what_ive_found_for_those_of_you_comparing/ | johnzakma10 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i38m86 | false | null | t3_1i38m86 | /r/LocalLLaMA/comments/1i38m86/heres_what_ive_found_for_those_of_you_comparing/ | false | false | self | 0 | {'enabled': False, 'images': [{'id': '1_MnsoBOjHUVlBv8s1AW8GF3ZoHqy4Q7Cx8Vh-5po64', 'resolutions': [{'height': 23, 'url': 'https://external-preview.redd.it/qucmYrGLR_ezD9eMXgpepPDC5n8MtQ-JNXioY_ynCHg.jpg?width=108&crop=smart&auto=webp&s=5d3f084b1f24c6be1b219ed06d50ede11039ae20', 'width': 108}, {'height': 47, 'url': 'https://external-preview.redd.it/qucmYrGLR_ezD9eMXgpepPDC5n8MtQ-JNXioY_ynCHg.jpg?width=216&crop=smart&auto=webp&s=4c4c27a0375b804db5d90bf12bf5c57a81b64386', 'width': 216}], 'source': {'height': 60, 'url': 'https://external-preview.redd.it/qucmYrGLR_ezD9eMXgpepPDC5n8MtQ-JNXioY_ynCHg.jpg?auto=webp&s=58df702c38afd9cce5d0d8f1b6181031aa15e77b', 'width': 272}, 'variants': {}}]} |
How do you guys use Open Source models in your workplace? I wish to start using them at my workplace. | 1 | [removed] | 2025-01-17T05:52:50 | https://www.reddit.com/r/LocalLLaMA/comments/1i39rn7/how_do_you_guys_use_open_source_models_in_your/ | Existing-Pay7076 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i39rn7 | false | null | t3_1i39rn7 | /r/LocalLLaMA/comments/1i39rn7/how_do_you_guys_use_open_source_models_in_your/ | false | false | self | 1 | null |
Astrologer & Psychic Spiritual Healer Fortune Teller | 1 | [removed] | 2025-01-17T06:32:09 | https://www.reddit.com/r/LocalLLaMA/comments/1i3acsd/astrologer_psychic_spiritual_healer_fortune_teller/ | Spirited_Tourist_565 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3acsd | false | null | t3_1i3acsd | /r/LocalLLaMA/comments/1i3acsd/astrologer_psychic_spiritual_healer_fortune_teller/ | true | false | spoiler | 1 | null |
Problem running f5 tts on pinokio | 1 | 2025-01-17T06:35:54 | Loves_to_analyse | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1i3aeqe | false | null | t3_1i3aeqe | /r/LocalLLaMA/comments/1i3aeqe/problem_running_f5_tts_on_pinokio/ | false | false | 1 | {'enabled': True, 'images': [{'id': 'dUp_FJTnvNK1y-L5Jyj2CeeyEL5k7_G1Yj2G7WQ5aFs', 'resolutions': [{'height': 49, 'url': 'https://preview.redd.it/hvvfmzoi1ide1.jpeg?width=108&crop=smart&auto=webp&s=b13f86a540e56ba52d82180a4440f889390441a3', 'width': 108}, {'height': 99, 'url': 'https://preview.redd.it/hvvfmzoi1ide1.jpeg?width=216&crop=smart&auto=webp&s=ac7b3b0e3582acf8276ab84763b16b5eaf54ac69', 'width': 216}, {'height': 147, 'url': 'https://preview.redd.it/hvvfmzoi1ide1.jpeg?width=320&crop=smart&auto=webp&s=796082f99bf27bb29558efe33095f23c059e9403', 'width': 320}, {'height': 295, 'url': 'https://preview.redd.it/hvvfmzoi1ide1.jpeg?width=640&crop=smart&auto=webp&s=50b90a1486e602fc4e2ee44d2ed25f811826c2de', 'width': 640}, {'height': 443, 'url': 'https://preview.redd.it/hvvfmzoi1ide1.jpeg?width=960&crop=smart&auto=webp&s=d52cfd41357d859b113d0b9bae6e3e06d204a99e', 'width': 960}, {'height': 498, 'url': 'https://preview.redd.it/hvvfmzoi1ide1.jpeg?width=1080&crop=smart&auto=webp&s=74150060868d2247e6f8b82b10390635988e1d7a', 'width': 1080}], 'source': {'height': 2136, 'url': 'https://preview.redd.it/hvvfmzoi1ide1.jpeg?auto=webp&s=90a0f7a92d67e47f1837a1729a05e14a7b18ba9a', 'width': 4624}, 'variants': {}}]} |
|||
Since I can't find similar subreddit for text-to-video unlike LLM, gonna ask here. How is temporal consistency solved? | 1 | [removed] | 2025-01-17T06:54:36 | https://www.reddit.com/r/LocalLLaMA/comments/1i3anxo/since_i_cant_find_similar_subreddit_for/ | Snoo_64233 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3anxo | false | null | t3_1i3anxo | /r/LocalLLaMA/comments/1i3anxo/since_i_cant_find_similar_subreddit_for/ | false | false | self | 1 | null |
What is the best free AI for assisting with coding? | 1 | [removed] | 2025-01-17T07:00:31 | https://www.reddit.com/r/LocalLLaMA/comments/1i3aquh/what_is_the_best_free_ai_for_assisting_with_coding/ | mmahdiSZ | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3aquh | false | null | t3_1i3aquh | /r/LocalLLaMA/comments/1i3aquh/what_is_the_best_free_ai_for_assisting_with_coding/ | false | false | self | 1 | null |
OpenWebUI Canvas Implementation -- Coming Soon! (Better Artifacts) | 232 | [C# and XML View](https://preview.redd.it/ytezb1q05ide1.png?width=1862&format=png&auto=webp&s=93364222443da5f695a745265842c91ee604d9e5)
[Design View](https://preview.redd.it/1ttzjm4s5ide1.png?width=1862&format=png&auto=webp&s=bd00eb16ef20e090d9f5ebee0d69f48c4f3b8bf0)
[Code VIew](https://preview.redd.it/7tj92xav5ide1.png?width=1749&format=png&auto=webp&s=81d8f9dec9bd3575fb4fc4ea8d399627b2eacd4a)
Hi all! I'm implementing Canvas (beefing up Artifacts) on OpenWebUI.
This was my only issue ever with OpenWebUI, just the very limited canvas feature (only restricted to HTML, CSS, JavaScript and SVG).
I've expanded support for the following languages:
C#, Python, Java, PHP, Ruby, Bash, Shell, AppleScript, SQL, JSON, XML, YAML, Markdown, HTML
If I'm missing one feel free to comment it! It's super easy to add at this point.
Another notable feature I'm adding is to switch between Design view and Code view for web design.
I'm super close to finishing! I just need to clean it up and visualize/track changes between revisions. Expect my pull request it in the next couple of weeks!
| 2025-01-17T07:02:43 | https://www.reddit.com/r/LocalLLaMA/comments/1i3as1m/openwebui_canvas_implementation_coming_soon/ | maxwell321 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3as1m | false | null | t3_1i3as1m | /r/LocalLLaMA/comments/1i3as1m/openwebui_canvas_implementation_coming_soon/ | false | false | 232 | null |
|
New framework aims to mimic human thinking for writing long-form content (OmniThink) | 44 | Sharing a paper about OmniThink - an approach that tries to replicate how humans write long-form content. The framework focuses on continuous reflection and exploration, similar to how we gather information and refine our understanding when writing detailed articles.
(Not affiliated with the authors)
The paper's style reminds me of Google Deep Research's functionality. I couldn't get their online demo to work, but the ideas in the paper are worth checking out, IMO. I will spend some time on their repo to see if that will work out of the box.
Paper: [https://huggingface.co/papers/2501.09751](https://huggingface.co/papers/2501.09751)
Project page: [https://zjunlp.github.io/project/OmniThink/](https://zjunlp.github.io/project/OmniThink/)
GitHub: [https://github.com/zjunlp/OmniThink](https://github.com/zjunlp/OmniThink)
https://preview.redd.it/alrt6fyh9ide1.png?width=3875&format=png&auto=webp&s=6a41e77eac565e5bf61deeaae9c0de535fb45feb
| 2025-01-17T07:22:39 | https://www.reddit.com/r/LocalLLaMA/comments/1i3b1jb/new_framework_aims_to_mimic_human_thinking_for/ | emanuilov | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3b1jb | false | null | t3_1i3b1jb | /r/LocalLLaMA/comments/1i3b1jb/new_framework_aims_to_mimic_human_thinking_for/ | false | false | 44 | {'enabled': False, 'images': [{'id': '2kae0vsjZm2286qrNI1XgJ7bmiMgWKJm_7xg7QVN4QM', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/P3wPulsj-vbHIfL8pdoJemWboTREaTu--SoaotPYjzU.jpg?width=108&crop=smart&auto=webp&s=5946e3d2b7788e9a5818d1a12ca54951538b74e8', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/P3wPulsj-vbHIfL8pdoJemWboTREaTu--SoaotPYjzU.jpg?width=216&crop=smart&auto=webp&s=132120dcae05cc07c350cd56f52c6cb262665efe', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/P3wPulsj-vbHIfL8pdoJemWboTREaTu--SoaotPYjzU.jpg?width=320&crop=smart&auto=webp&s=0a937d4d70066aa757a39f32327aa075c7affea3', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/P3wPulsj-vbHIfL8pdoJemWboTREaTu--SoaotPYjzU.jpg?width=640&crop=smart&auto=webp&s=098b6934967a73dbc796419d5bd3b3397ed04814', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/P3wPulsj-vbHIfL8pdoJemWboTREaTu--SoaotPYjzU.jpg?width=960&crop=smart&auto=webp&s=d8323b8d8eb6a0b0819972ebae2c9cf27a8d8270', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/P3wPulsj-vbHIfL8pdoJemWboTREaTu--SoaotPYjzU.jpg?width=1080&crop=smart&auto=webp&s=225057b22efbaf2506fbe7a9788dd681447604af', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/P3wPulsj-vbHIfL8pdoJemWboTREaTu--SoaotPYjzU.jpg?auto=webp&s=f33add2ddabcfeb6d87d534b6a7ef0dd234b8f2a', 'width': 1200}, 'variants': {}}]} |
|
Models for shorter context | 0 | Recent trends have been to push for larger context windows and to compensate for the ballooning VRAM and compute costs of longer contexts by using techniques such as GQA etc.
But let's say you have a task that requires only 4k or 8k of context. And you want to have the best performance possible for this context size.
Are there models that perform better within this limited context or a way of tuning existing models to perform better with a 4k or 8k context window? | 2025-01-17T07:58:56 | https://www.reddit.com/r/LocalLLaMA/comments/1i3bieb/models_for_shorter_context/ | DeltaSqueezer | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3bieb | false | null | t3_1i3bieb | /r/LocalLLaMA/comments/1i3bieb/models_for_shorter_context/ | false | false | self | 0 | null |
Best vision model via API? | 1 | Can somebody please suggest the best vision model which is available for commercial use via API outside of GPT-4o? I find it’s censored in reading biometric data or helping in medical analysis.
Thank you! | 2025-01-17T08:28:07 | https://www.reddit.com/r/LocalLLaMA/comments/1i3bvzv/best_vision_model_via_api/ | 99OG121314 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3bvzv | false | null | t3_1i3bvzv | /r/LocalLLaMA/comments/1i3bvzv/best_vision_model_via_api/ | false | false | self | 1 | null |
"Can't live without tool" for LLM datasets? | 20 | I thought it would be interesting to know what tool people absolutely love using when it comes to LLM training - more specifically creating and preparing datasets?
Also, feel free to just share any knowledge you feel is a "cheatsheet" or too good to be true?
Have a great weekend! | 2025-01-17T09:07:39 | https://www.reddit.com/r/LocalLLaMA/comments/1i3cdws/cant_live_without_tool_for_llm_datasets/ | Secure_Archer_1529 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3cdws | false | null | t3_1i3cdws | /r/LocalLLaMA/comments/1i3cdws/cant_live_without_tool_for_llm_datasets/ | false | false | self | 20 | null |
Hugging Face Spaces make the perfect agent tools! | 1 | [removed] | 2025-01-17T09:17:55 | [deleted] | 1970-01-01T00:00:00 | 0 | {} | 1i3cird | false | null | t3_1i3cird | /r/LocalLLaMA/comments/1i3cird/hugging_face_spaces_make_the_perfect_agent_tools/ | false | false | default | 1 | null |
||
Thinking about finetuning an SLM (i.e 0.5B, 2B) for PII a as a way to learn. Worth the shot? | 5 | Hello!
I posted something similar a few months ago, but after evaluating the quality of the new SLM models, I think it would make sense to undertake a project to finetune a model specifically for PII. Additionally, perhaps developing a Docker container with a complete solution incorporating the model, agentic behavior, and possibly [Presidio](https://microsoft.github.io/presidio/) could be beneficial.
Could be a good way to learn all the finetuning pipeline with [unsloth](https://unsloth.ai/)?
Tell me what you think. Thank you!
https://preview.redd.it/wrdfedt0yide1.png?width=3190&format=png&auto=webp&s=98842a4696a8cf4ac8780dc0749565e32856bfb1
| 2025-01-17T09:39:23 | https://www.reddit.com/r/LocalLLaMA/comments/1i3csqz/thinking_about_finetuning_an_slm_ie_05b_2b_for/ | GeorgiaWitness1 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3csqz | false | null | t3_1i3csqz | /r/LocalLLaMA/comments/1i3csqz/thinking_about_finetuning_an_slm_ie_05b_2b_for/ | false | false | 5 | null |
|
Korea AI Chip - DEEPX NPU . Price? Under 50$ . Better that GPU? | 0 | Hello.
This will be game changer? Better that GPU?
DEEPX NPU. Edge Computing
Website: https://deepx.ai/
| 2025-01-17T09:50:04 | https://youtu.be/5aJNJLRsVlk | bi4key | youtu.be | 1970-01-01T00:00:00 | 0 | {} | 1i3cxm0 | false | {'oembed': {'author_name': 'ipXchange', 'author_url': 'https://www.youtube.com/@ipXchange', 'height': 200, 'html': '<iframe width="356" height="200" src="https://www.youtube.com/embed/5aJNJLRsVlk?feature=oembed&enablejsapi=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen title="Real-Time Edge Computing for Under $50"></iframe>', 'provider_name': 'YouTube', 'provider_url': 'https://www.youtube.com/', 'thumbnail_height': 360, 'thumbnail_url': 'https://i.ytimg.com/vi/5aJNJLRsVlk/hqdefault.jpg', 'thumbnail_width': 480, 'title': 'Real-Time Edge Computing for Under $50', 'type': 'video', 'version': '1.0', 'width': 356}, 'type': 'youtube.com'} | t3_1i3cxm0 | /r/LocalLLaMA/comments/1i3cxm0/korea_ai_chip_deepx_npu_price_under_50_better/ | false | false | 0 | {'enabled': False, 'images': [{'id': 'wIq8jgchQyOcWX6QmgFjaZ8Fzi-ddGFxOIfHp3LTMLo', 'resolutions': [{'height': 81, 'url': 'https://external-preview.redd.it/P-NYeqvu1eSDu3ZqaeWja5plMoJW5E-Wg-nWjjs5CuU.jpg?width=108&crop=smart&auto=webp&s=7243543f136f2d28e6290a4facfaff55e66887d0', 'width': 108}, {'height': 162, 'url': 'https://external-preview.redd.it/P-NYeqvu1eSDu3ZqaeWja5plMoJW5E-Wg-nWjjs5CuU.jpg?width=216&crop=smart&auto=webp&s=6652566287d7e84ba7ed4b3061e68aec5cf40b0a', 'width': 216}, {'height': 240, 'url': 'https://external-preview.redd.it/P-NYeqvu1eSDu3ZqaeWja5plMoJW5E-Wg-nWjjs5CuU.jpg?width=320&crop=smart&auto=webp&s=80557a815c31a1454adfc473c446fa4d55b69fdb', 'width': 320}], 'source': {'height': 360, 'url': 'https://external-preview.redd.it/P-NYeqvu1eSDu3ZqaeWja5plMoJW5E-Wg-nWjjs5CuU.jpg?auto=webp&s=888fa16e521be4178c9baaf04bb9686d1edb2a8b', 'width': 480}, 'variants': {}}]} |
|
Hugging Face Spaces make the perfect agent tools! | 16 | Figured out that you could use Gradio based spaces on the hub as tools for agents. I don't get why everyone isn't doing this.
https://preview.redd.it/etq92tij3jde1.png?width=1092&format=png&auto=webp&s=baf38c94e6240885d8d4d02953e16f9414a12a02
Made a guide here: [https://huggingface.co/blog/burtenshaw/gradio-spaces-agent-tools](https://huggingface.co/blog/burtenshaw/gradio-spaces-agent-tools) | 2025-01-17T10:09:40 | https://www.reddit.com/r/LocalLLaMA/comments/1i3d6t0/hugging_face_spaces_make_the_perfect_agent_tools/ | Zealousideal-Cut590 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3d6t0 | false | null | t3_1i3d6t0 | /r/LocalLLaMA/comments/1i3d6t0/hugging_face_spaces_make_the_perfect_agent_tools/ | false | false | 16 | null |
|
InternLM3 Open Source: Achieving High-Performance Models with 4T Data | 1 | [removed] | 2025-01-17T10:16:46 | https://www.reddit.com/r/LocalLLaMA/comments/1i3da6n/internlm3_open_source_achieving_highperformance/ | InternLM | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3da6n | false | null | t3_1i3da6n | /r/LocalLLaMA/comments/1i3da6n/internlm3_open_source_achieving_highperformance/ | false | false | 1 | null |
|
Table extraction from Finance PDF's | 10 | By any chance is there any way which is 100% accurate to extract tabular data from finance pdfs which basically contains balance sheets and tables.
I tried everything pytesseract , camelot , tabula , Microsoft table transformer , but there isnt any accuracy with proper headers , empty columns.
I even tried openai's assistant api with code\_interpreter as tool but that also lacks with the accuracy.
Anyone has ever tried to work on this solution ?? | 2025-01-17T10:22:21 | https://www.reddit.com/r/LocalLLaMA/comments/1i3dcxz/table_extraction_from_finance_pdfs/ | Maleficent_Repair359 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3dcxz | false | null | t3_1i3dcxz | /r/LocalLLaMA/comments/1i3dcxz/table_extraction_from_finance_pdfs/ | false | false | self | 10 | null |
Help me choose a model | 1 | [removed] | 2025-01-17T10:44:20 | https://www.reddit.com/r/LocalLLaMA/comments/1i3dnv2/help_me_choose_a_model/ | Internal_Pass_2227 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3dnv2 | false | null | t3_1i3dnv2 | /r/LocalLLaMA/comments/1i3dnv2/help_me_choose_a_model/ | false | false | self | 1 | null |
Looking for a LLM that I can run on my iPhone for learning German | 1 | [removed] | 2025-01-17T11:01:12 | https://www.reddit.com/r/LocalLLaMA/comments/1i3dwgo/looking_for_a_llm_that_i_can_run_on_my_iphone_for/ | chikyiuting | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3dwgo | false | null | t3_1i3dwgo | /r/LocalLLaMA/comments/1i3dwgo/looking_for_a_llm_that_i_can_run_on_my_iphone_for/ | false | false | self | 1 | null |
Top LLM Benchmarking Platforms - Need Suggestions | 1 | Hi, I have been looking for some popular LLM Benchmarking and Evaluation platforms and some of my tech friends recommended me Athina AI, Deep Eval, Confident AI.
Any more suggestions? | 2025-01-17T11:16:05 | https://www.reddit.com/r/LocalLLaMA/comments/1i3e4h3/top_llm_benchmarking_platforms_need_suggestions/ | Sam_Tech1 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3e4h3 | false | null | t3_1i3e4h3 | /r/LocalLLaMA/comments/1i3e4h3/top_llm_benchmarking_platforms_need_suggestions/ | false | false | self | 1 | null |
HTTP 404 Not Found from ... | 1 | [removed] | 2025-01-17T11:37:13 | https://www.reddit.com/r/LocalLLaMA/comments/1i3eft3/http_404_not_found_from/ | Hefty_Cup_8160 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3eft3 | false | null | t3_1i3eft3 | /r/LocalLLaMA/comments/1i3eft3/http_404_not_found_from/ | false | false | 1 | null |
|
Anyone collecting numbers on efficiency / performance in terms of tokens-per-watt? | LLM-efficiency leaderboard? | 3 | Hey everyone! Basically just the title - anyone know if there's any data out there on e.g. max tokens-per-watt of a RaspPi vs, say, a 4090? I found [this post](https://www.reddit.com/r/LocalLLaMA/comments/1gb8lmp/inference_comparing_tokens_per_watt_4090_vs_apple/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button) from a few months back but it didn't have much actual data, just anecdotal stuff. I'm kind assuming that if any kind of LLM-efficiency leaderboard **did** exist I'd probably be able to find it, but a quick Google hasn't yielded anything fruitful either.
Would appreciate if anyone's got any leads / would be willing to share any numbers 🙌 | 2025-01-17T11:51:17 | https://www.reddit.com/r/LocalLLaMA/comments/1i3enfs/anyone_collecting_numbers_on_efficiency/ | mark-lord | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3enfs | false | null | t3_1i3enfs | /r/LocalLLaMA/comments/1i3enfs/anyone_collecting_numbers_on_efficiency/ | false | false | self | 3 | null |
Motherboard for dual gpus? | 1 | [removed] | 2025-01-17T11:58:22 | https://www.reddit.com/r/LocalLLaMA/comments/1i3erdz/motherboard_for_dual_gpus/ | XPEZNAZ | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3erdz | false | null | t3_1i3erdz | /r/LocalLLaMA/comments/1i3erdz/motherboard_for_dual_gpus/ | false | false | self | 1 | null |
Cloud the 360M model learn reasoning ? | 0 | Show your perspective :) | 2025-01-17T12:02:12 | https://www.reddit.com/r/LocalLLaMA/comments/1i3etqv/cloud_the_360m_model_learn_reasoning/ | absurd-dream-studio | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3etqv | false | null | t3_1i3etqv | /r/LocalLLaMA/comments/1i3etqv/cloud_the_360m_model_learn_reasoning/ | false | false | self | 0 | null |
What is the best VS code AI extension? | 1 | [removed] | 2025-01-17T12:46:31 | https://www.reddit.com/r/LocalLLaMA/comments/1i3fkh1/what_is_the_best_vs_code_ai_extension/ | SkylarNox | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3fkh1 | false | null | t3_1i3fkh1 | /r/LocalLLaMA/comments/1i3fkh1/what_is_the_best_vs_code_ai_extension/ | false | false | self | 1 | null |
Laptop LLM performance - beware of the power settings! | 51 | It's pity that I did such a lame negligence, but want to share with you, in case someone struggles with the same issue.
Both me and the wife have Lenovo gaming laptops:
1. Rizen 5, 16GB RAM, 3050ti 4GB
2. i5, 16GB RAM, 4060 8GB
Logically, if a model fits entirely in the VRAM, the machine 2 runs it noticeble faster. BUT, everything beyond 7B which is partially offloaded in VRAM, practically goes with less than 0.2T/s and takes 2-3 minutes to output the first token on the machine 2! While machine 1 runs Qwen 2.5 14B quite acceptable with around 2T/s.
I was changing nVidia/CUDA drivers, settings of llama.cpp - nothing helped. Till I checked the "power settings" of Windows and changed the presets from "balanced" to "performance". It was the CPU/RAM of the machine which killed all the fun. Now I get 5-10 T/s with 14B model and 26/49 layers to GPU. | 2025-01-17T12:48:10 | https://www.reddit.com/r/LocalLLaMA/comments/1i3fli7/laptop_llm_performance_beware_of_the_power/ | YordanTU | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3fli7 | false | null | t3_1i3fli7 | /r/LocalLLaMA/comments/1i3fli7/laptop_llm_performance_beware_of_the_power/ | false | false | self | 51 | null |
2025 Hardware Options for 70B models at Q8? | 1 | [removed] | 2025-01-17T13:22:09 | https://www.reddit.com/r/LocalLLaMA/comments/1i3g7q4/2025_hardware_options_for_70b_models_at_q8/ | dwrz | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3g7q4 | false | null | t3_1i3g7q4 | /r/LocalLLaMA/comments/1i3g7q4/2025_hardware_options_for_70b_models_at_q8/ | false | false | self | 1 | null |
Anyone has a succesfully running local self hosted LLM utilizing local RAG system? How did you do it? | 1 | [removed] | 2025-01-17T13:36:39 | https://www.reddit.com/r/LocalLLaMA/comments/1i3ghs9/anyone_has_a_succesfully_running_local_self/ | peacepleaseluv | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3ghs9 | false | null | t3_1i3ghs9 | /r/LocalLLaMA/comments/1i3ghs9/anyone_has_a_succesfully_running_local_self/ | false | false | self | 1 | null |
Llm for translation | 9 | Hi I recently installed subtitle edit and the newer version has a llm translation option, I have 32gb of ram and 8 gb of vram what is the best model to install to ollama for this job?
Better to go with something lighter like Gemma 2 or opting for lighter quantization of llama 3.3?
Thx for the help. | 2025-01-17T14:06:26 | https://www.reddit.com/r/LocalLLaMA/comments/1i3h313/llm_for_translation/ | InternalMode8159 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3h313 | false | null | t3_1i3h313 | /r/LocalLLaMA/comments/1i3h313/llm_for_translation/ | false | false | self | 9 | null |
Attend - Proof of Concept | 39 | I've gotten fed up with hoping on the computer to do one thing, and doing other stuff instead.
I'm building Attend so that our devices can help us dedicate our time and attention on what matters to us, instead of what someone else thinks is best.
Right now, it is a voice assistant that uses a vision LLM to "watch" your screen and help you get back on track if what you're doing isn't aligned with what you said you wanted to do.
I've got some work to do on the workflows and prompts to reduce false positives, but it "works" and I'm very excited about it!
I'd like to get this down to a single 3090, but two seems pretty feasible. Part of the problem most open weight vision language models are garbage with 4K images/screenshots. Qwen2-VL seems to be an exception, but it (especially the 7B) is garbage when it comes to driving the workflows behind Attend. So, I've just been using Qwen2-VL-7B-Instruct and Llama-3.3 at 8-bit as I get it working. I'd love to hear suggestions for minimizing VRAM (Intern2\_5-VL also seems to handle 4K alright, but I haven't tested it enough on the workflows).
Attend interfaces with all models using OpenAI compatable API calls. So, you should be able to use the cloud, if you're into that kinda thing... You could also take a hybrid approach. I think you could get the STT and vision LLM into 16GB VRAM and run that locally. Piper TTS runs well on CPU. You could then use a cloud model just for the text LLM and keep the most sensitive stuff (screenshots!) local.
Check it out the code [https://github.com/hyperfocAIs/Attend/](https://github.com/hyperfocAIs/Attend/) and a proof of concept video [https://youtu.be/PETrY540zMM](https://youtu.be/PETrY540zMM) | 2025-01-17T14:12:36 | https://www.reddit.com/r/LocalLLaMA/comments/1i3h7hs/attend_proof_of_concept/ | Pedalnomica | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3h7hs | false | null | t3_1i3h7hs | /r/LocalLLaMA/comments/1i3h7hs/attend_proof_of_concept/ | false | false | self | 39 | {'enabled': False, 'images': [{'id': '1Gn-P5acoEExl5aIYNCZLbJySDb-cAwmCuzkLs4pELQ', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/4ZP0JefOBQj5iWrXQEEaRp2ybz17gH-cE2g-WXlA5-0.jpg?width=108&crop=smart&auto=webp&s=f4e96fc1698e3be152d11a98706961aa7a522d5a', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/4ZP0JefOBQj5iWrXQEEaRp2ybz17gH-cE2g-WXlA5-0.jpg?width=216&crop=smart&auto=webp&s=723767bb79156541d613addef6a18b9295bb8d94', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/4ZP0JefOBQj5iWrXQEEaRp2ybz17gH-cE2g-WXlA5-0.jpg?width=320&crop=smart&auto=webp&s=6f51bf214b3d116533973d8c0e2466c9101773f1', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/4ZP0JefOBQj5iWrXQEEaRp2ybz17gH-cE2g-WXlA5-0.jpg?width=640&crop=smart&auto=webp&s=34ea13299c3460b389ceacd21e80f0da77a76482', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/4ZP0JefOBQj5iWrXQEEaRp2ybz17gH-cE2g-WXlA5-0.jpg?width=960&crop=smart&auto=webp&s=fe31bb4466342a982f59d03e47e771d57e07eddd', 'width': 960}, {'height': 540, 'url': 'https://external-preview.redd.it/4ZP0JefOBQj5iWrXQEEaRp2ybz17gH-cE2g-WXlA5-0.jpg?width=1080&crop=smart&auto=webp&s=ea7d8aa07714fe1e4b08a22d925f2d9b5ba83148', 'width': 1080}], 'source': {'height': 600, 'url': 'https://external-preview.redd.it/4ZP0JefOBQj5iWrXQEEaRp2ybz17gH-cE2g-WXlA5-0.jpg?auto=webp&s=a5be17dd71f2533e6abf42800d7add45bcc1a32a', 'width': 1200}, 'variants': {}}]} |
Whats the simplest form of training data attack that one can try on BERT like models? | 1 | Im referring to membership inference attack to identify whether a given data sample was used in the BERT model training data. | 2025-01-17T14:14:26 | https://www.reddit.com/r/LocalLLaMA/comments/1i3h8tx/whats_the_simplest_form_of_training_data_attack/ | Lazy_Wedding_1383 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3h8tx | false | null | t3_1i3h8tx | /r/LocalLLaMA/comments/1i3h8tx/whats_the_simplest_form_of_training_data_attack/ | false | false | self | 1 | null |
What do I need to use to lip sync with audio just a few seconds / segment of a video? | 1 | [removed] | 2025-01-17T14:26:25 | https://www.reddit.com/r/LocalLLaMA/comments/1i3hhty/what_do_i_need_to_use_to_lip_sync_with_audio_just/ | WarmSummerDrink | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3hhty | false | null | t3_1i3hhty | /r/LocalLLaMA/comments/1i3hhty/what_do_i_need_to_use_to_lip_sync_with_audio_just/ | false | false | self | 1 | null |
Does AI TOPS Impact AI Inference and Training Speeds? Comparing GPUs in the Charts | 1 | 2025-01-17T14:46:11 | One_Imagination_5581 | i.redd.it | 1970-01-01T00:00:00 | 0 | {} | 1i3hwxt | false | null | t3_1i3hwxt | /r/LocalLLaMA/comments/1i3hwxt/does_ai_tops_impact_ai_inference_and_training/ | false | false | 1 | {'enabled': True, 'images': [{'id': '7aREA8rgT2nWTZQKNTo9A4jpxOelFxGJ0K3mLUb00DI', 'resolutions': [{'height': 82, 'url': 'https://preview.redd.it/068yj4uwgkde1.jpeg?width=108&crop=smart&auto=webp&s=b3afb32581c2818cd5c8ae7effd85ebff6782bde', 'width': 108}, {'height': 165, 'url': 'https://preview.redd.it/068yj4uwgkde1.jpeg?width=216&crop=smart&auto=webp&s=da10d6088578256b786f18fb8e7501c298970dbd', 'width': 216}, {'height': 245, 'url': 'https://preview.redd.it/068yj4uwgkde1.jpeg?width=320&crop=smart&auto=webp&s=318df70763e3e207b7df3b60c1f324f69b5944c6', 'width': 320}, {'height': 490, 'url': 'https://preview.redd.it/068yj4uwgkde1.jpeg?width=640&crop=smart&auto=webp&s=6846e83652a1529f13373ac0b2e9d4966cff9fdc', 'width': 640}], 'source': {'height': 698, 'url': 'https://preview.redd.it/068yj4uwgkde1.jpeg?auto=webp&s=9dd5688fd3eceea2c8390d37bf5eaf4f64a7c6ad', 'width': 911}, 'variants': {}}]} |
|||
[REPOST]Linux 6.14 will have amdxdna! The Ryzen AI NPU driver | 29 | What will this mean for amd cards and AI inference? | 2025-01-17T15:17:23 | https://www.reddit.com/r/LocalLLaMA/comments/1i3ilu3/repostlinux_614_will_have_amdxdna_the_ryzen_ai/ | KillerX629 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3ilu3 | false | null | t3_1i3ilu3 | /r/LocalLLaMA/comments/1i3ilu3/repostlinux_614_will_have_amdxdna_the_ryzen_ai/ | false | false | self | 29 | null |
NVIDIA RTX 5090: Limited Availability and Restrictions on AI and Multi-GPU | 0 | According to a recent article from El Chapuzas Informático, NVIDIA’s upcoming RTX 50 series GPUs will not only be released in limited quantities but will also include built-in restrictions on certain functionalities. These include reduced performance for AI workloads, cryptocurrency mining, and the use of multiple GPUs in the same setup. | 2025-01-17T15:21:45 | https://elchapuzasinformatico.com/2025/01/nvidia-rtx-50-limitadas-tiendas-capadas-ia-criptomineria-multi-gpu/ | Spiritual_Tie_5574 | elchapuzasinformatico.com | 1970-01-01T00:00:00 | 0 | {} | 1i3ipgs | false | null | t3_1i3ipgs | /r/LocalLLaMA/comments/1i3ipgs/nvidia_rtx_5090_limited_availability_and/ | false | false | 0 | {'enabled': False, 'images': [{'id': 'r788YZJQERdLVJ5SY6QfV0F8vzCqCClewZLVXsMpQ2U', 'resolutions': [{'height': 54, 'url': 'https://external-preview.redd.it/bteDT1wTCKTt11oDOxCHMBb98egjkfRqBELv99v2-pQ.jpg?width=108&crop=smart&auto=webp&s=d806a82adec18df58cfc812006581a4efc702a7e', 'width': 108}, {'height': 108, 'url': 'https://external-preview.redd.it/bteDT1wTCKTt11oDOxCHMBb98egjkfRqBELv99v2-pQ.jpg?width=216&crop=smart&auto=webp&s=f849176cc4919bbca0aa05f2a939a35e9c1228d0', 'width': 216}, {'height': 160, 'url': 'https://external-preview.redd.it/bteDT1wTCKTt11oDOxCHMBb98egjkfRqBELv99v2-pQ.jpg?width=320&crop=smart&auto=webp&s=a349625a828bbb738c80c81f22f1f8fff3d43cc1', 'width': 320}, {'height': 320, 'url': 'https://external-preview.redd.it/bteDT1wTCKTt11oDOxCHMBb98egjkfRqBELv99v2-pQ.jpg?width=640&crop=smart&auto=webp&s=289505e7d1bdf4bb60380e17eb9f3257cce959d5', 'width': 640}, {'height': 480, 'url': 'https://external-preview.redd.it/bteDT1wTCKTt11oDOxCHMBb98egjkfRqBELv99v2-pQ.jpg?width=960&crop=smart&auto=webp&s=92e50a73c3892cf840044f94feba5c0600a35049', 'width': 960}], 'source': {'height': 500, 'url': 'https://external-preview.redd.it/bteDT1wTCKTt11oDOxCHMBb98egjkfRqBELv99v2-pQ.jpg?auto=webp&s=f2d35592e4db842c8fecaddc3a3e19429cf62e63', 'width': 1000}, 'variants': {}}]} |
|
"I/We/They Couldn't Help But..." Repeating LLM Phrasing? | 16 | >The spacecraft's sensors detected a safe landing spot near a lush forest, and the pilot navigated the ship towards the area. As they approached, they couldn't help but notice the array of exotic flora that thrived in the region.
To those that use LLMs often, I think you know of this affect.
I've actually added "Don't use the words '*I couldn't help but*' in your output" and have still had the LLM put the phrase in there, almost like it worked like the "don't think of an elephant," concept for humans. | 2025-01-17T15:27:12 | https://www.reddit.com/r/LocalLLaMA/comments/1i3itva/iwethey_couldnt_help_but_repeating_llm_phrasing/ | Jattoe | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3itva | false | null | t3_1i3itva | /r/LocalLLaMA/comments/1i3itva/iwethey_couldnt_help_but_repeating_llm_phrasing/ | false | false | self | 16 | null |
Built this PlayPixAI app with Qwen2-VL in under 15 minutes! | 1 | [removed] | 2025-01-17T15:35:06 | https://www.reddit.com/r/LocalLLaMA/comments/1i3j04z/built_this_playpixai_app_with_qwen2vl_in_under_15/ | codes_astro | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3j04z | false | null | t3_1i3j04z | /r/LocalLLaMA/comments/1i3j04z/built_this_playpixai_app_with_qwen2vl_in_under_15/ | false | false | 1 | null |
|
Best Setup PC Config For Llama-3.1-8B | 1 | [removed] | 2025-01-17T15:35:58 | https://www.reddit.com/r/LocalLLaMA/comments/1i3j0te/best_setup_pc_config_for_llama318b/ | AvaloxBR | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3j0te | false | null | t3_1i3j0te | /r/LocalLLaMA/comments/1i3j0te/best_setup_pc_config_for_llama318b/ | false | false | self | 1 | null |
Finetuning Llama for a step by step synthesis | 1 | [removed] | 2025-01-17T16:02:21 | https://www.reddit.com/r/LocalLLaMA/comments/1i3jmpr/finetuning_llama_for_a_step_by_step_synthesis/ | No-Judge3265 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3jmpr | false | null | t3_1i3jmpr | /r/LocalLLaMA/comments/1i3jmpr/finetuning_llama_for_a_step_by_step_synthesis/ | false | false | self | 1 | null |
Fine tune llama on synthesis procedures | 1 | [removed] | 2025-01-17T16:04:04 | https://www.reddit.com/r/LocalLLaMA/comments/1i3jo7y/fine_tune_llama_on_synthesis_procedures/ | No-Judge3265 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3jo7y | false | null | t3_1i3jo7y | /r/LocalLLaMA/comments/1i3jo7y/fine_tune_llama_on_synthesis_procedures/ | false | false | self | 1 | null |
Ollama is using RAM despite having enough VRAM | 1 | [removed] | 2025-01-17T16:09:06 | https://www.reddit.com/r/LocalLLaMA/comments/1i3jskm/ollama_is_using_ram_despite_having_enough_vram/ | DamballaTun | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3jskm | false | null | t3_1i3jskm | /r/LocalLLaMA/comments/1i3jskm/ollama_is_using_ram_despite_having_enough_vram/ | false | false | 1 | null |
|
Ollama is using RAM despite having enough VRAM | 1 | [removed] | 2025-01-17T16:09:07 | https://www.reddit.com/r/LocalLLaMA/comments/1i3jsks/ollama_is_using_ram_despite_having_enough_vram/ | DamballaTun | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3jsks | false | null | t3_1i3jsks | /r/LocalLLaMA/comments/1i3jsks/ollama_is_using_ram_despite_having_enough_vram/ | false | false | self | 1 | null |
Ollama is loading a part of the model to RAM despite having limited VRAM | 1 | [removed] | 2025-01-17T16:11:15 | https://www.reddit.com/r/LocalLLaMA/comments/1i3jud8/ollama_is_loading_a_part_of_the_model_to_ram/ | DamballaTun | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3jud8 | false | null | t3_1i3jud8 | /r/LocalLLaMA/comments/1i3jud8/ollama_is_loading_a_part_of_the_model_to_ram/ | false | false | 1 | null |
|
AI Rig recommendations - up to $10k budget | 1 | [removed] | 2025-01-17T16:25:00 | https://www.reddit.com/r/LocalLLaMA/comments/1i3k5v6/ai_rig_recommendations_up_to_10k_budget/ | lord_denister | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3k5v6 | false | null | t3_1i3k5v6 | /r/LocalLLaMA/comments/1i3k5v6/ai_rig_recommendations_up_to_10k_budget/ | false | false | self | 1 | null |
Best Approach to Create MCQs from Large PDFs with Correct Answers as Ground Truth? | 5 | I’m working on generating multiple-choice questions (MCQs) from large PDFs (400-500 pages). The goal is to create a training dataset with correct answers as ground truth. My main concerns are: Efficiently extracting and summarizing content from such large PDFs to generate relevant MCQs, and add varying level of relevancy to test retrieval.
I’m considering using LLM for summarization and question generation, but I’m unsure about the best tools or frameworks to handle this effectively. Additionally, I’d appreciate any recommendations on where to start learning about this process (e.g., tutorials, courses, or resources). | 2025-01-17T16:38:45 | https://www.reddit.com/r/LocalLLaMA/comments/1i3khqj/best_approach_to_create_mcqs_from_large_pdfs_with/ | suns9 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3khqj | false | null | t3_1i3khqj | /r/LocalLLaMA/comments/1i3khqj/best_approach_to_create_mcqs_from_large_pdfs_with/ | false | false | self | 5 | null |
Is there a difference between chat and repeated calling from scratch? | 3 | When I do chat with a bot, it is like:
\- #0: <me writing>
\- #1 <LLM writing>
\- #2: <me writing>
\- #3 <LLM writing>
\- #4: <me writing>
\- #5 <LLM writing>
Is there any fundamental difference between that and calling the LLM with #0, then with the concatenation of #0 and #2 (or is it #0, #1, #2?), and then #0, #2, and #4 (or is it #0..#4?)
Is there any difference between the models, whether they respond significantly different ways? | 2025-01-17T16:46:27 | https://www.reddit.com/r/LocalLLaMA/comments/1i3kohb/is_there_a_difference_between_chat_and_repeated/ | yelling-at-clouds-40 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3kohb | false | null | t3_1i3kohb | /r/LocalLLaMA/comments/1i3kohb/is_there_a_difference_between_chat_and_repeated/ | false | false | self | 3 | null |
[Magnum/SE] LLama 3.3 70b | 57 | Hello again, folks!
We've got something a little different to share this time. It's not a full release or a new series as of yet, but more like an epilogue to the v4 series we released a few months back. DoctorShotgun wasn't entirely satisfied with how the large models in the series turned out, so he spent some more time in the lab - this time on the newer llama 3.3 model for a change:
[https://huggingface.co/Doctor-Shotgun/L3.3-70B-Magnum-v4-SE](https://huggingface.co/Doctor-Shotgun/L3.3-70B-Magnum-v4-SE)
This time, the model was trained as an rslora with recommendations from Gryphe of Mythomax fame, and it comes with the full set of adapter checkpoints for mergers and other experimenters to play around with ([available here](https://huggingface.co/Doctor-Shotgun/Magnum-v4-SE-70B-LoRA)). Preliminary testing suggests that rslora adequately style-transfers the classic Claude-y flavor of magnum to the llama 3.3 model.
In terms of changes to the data, the model doesn't deviate too far from the v4 series. The dataset includes some further cleaning of the RP log dataset used in v4, as well as the re-introduction of a subset of the data used in the v2 and earlier models. As per usual, the training config is linked from the model card in the spirit of open source.
No first-party quants are available at this time, but links to those created by well-known quanters are linked in the model description.
Hope you enjoy this belated New Years present, and stay tuned for what's to come! | 2025-01-17T16:54:07 | https://www.reddit.com/r/LocalLLaMA/comments/1i3kv1n/magnumse_llama_33_70b/ | lucyknada | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3kv1n | false | null | t3_1i3kv1n | /r/LocalLLaMA/comments/1i3kv1n/magnumse_llama_33_70b/ | false | false | self | 57 | {'enabled': False, 'images': [{'id': '_GNxGlqytIboTVafo63MP51m4Pre1VBSMvfwIZ7lyJs', 'resolutions': [{'height': 58, 'url': 'https://external-preview.redd.it/OulaTA0iLU_ZB0lP9Cybw9YSZVhXk9mcP-oILIJ_zrE.jpg?width=108&crop=smart&auto=webp&s=cd2cf07fc39d57dd8f8506343f9b84c9f30872d7', 'width': 108}, {'height': 116, 'url': 'https://external-preview.redd.it/OulaTA0iLU_ZB0lP9Cybw9YSZVhXk9mcP-oILIJ_zrE.jpg?width=216&crop=smart&auto=webp&s=c4239413e08903de9654b26ef3cf7ac08b937c12', 'width': 216}, {'height': 172, 'url': 'https://external-preview.redd.it/OulaTA0iLU_ZB0lP9Cybw9YSZVhXk9mcP-oILIJ_zrE.jpg?width=320&crop=smart&auto=webp&s=c1f5fb66f700cbee9c3b5a52a5abee888c778e7d', 'width': 320}, {'height': 345, 'url': 'https://external-preview.redd.it/OulaTA0iLU_ZB0lP9Cybw9YSZVhXk9mcP-oILIJ_zrE.jpg?width=640&crop=smart&auto=webp&s=cdbc5ac85044410820db02c5f1e39f08ed5842be', 'width': 640}, {'height': 518, 'url': 'https://external-preview.redd.it/OulaTA0iLU_ZB0lP9Cybw9YSZVhXk9mcP-oILIJ_zrE.jpg?width=960&crop=smart&auto=webp&s=ccb0787ab37955c25570941e370e1a5c050d9867', 'width': 960}, {'height': 583, 'url': 'https://external-preview.redd.it/OulaTA0iLU_ZB0lP9Cybw9YSZVhXk9mcP-oILIJ_zrE.jpg?width=1080&crop=smart&auto=webp&s=55a11538db534c8e84d6224d8e58746ebd097e5c', 'width': 1080}], 'source': {'height': 648, 'url': 'https://external-preview.redd.it/OulaTA0iLU_ZB0lP9Cybw9YSZVhXk9mcP-oILIJ_zrE.jpg?auto=webp&s=664ce2af7c75f353b4cbf93be700e8904a50259b', 'width': 1200}, 'variants': {}}]} |
How many documents do I need to create something useful? | 0 | I'm an attorney and I can't really put client data into ChatGPT. I was thinking about taking all of the cases and statutes (laws) and feeding them to a local LLM. It wouldn't be a ton of documents, probably in 3k range. Would this be feasible or would I need a lot more documents? This would just be for personal use. | 2025-01-17T17:42:03 | https://www.reddit.com/r/LocalLLaMA/comments/1i3m0h9/how_many_documents_do_i_need_to_create_something/ | irr1449 | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3m0h9 | false | null | t3_1i3m0h9 | /r/LocalLLaMA/comments/1i3m0h9/how_many_documents_do_i_need_to_create_something/ | false | false | self | 0 | null |
A local model recognizing price | 1 | [removed] | 2025-01-17T18:02:33 | https://www.reddit.com/r/LocalLLaMA/comments/1i3mi6e/a_local_model_recognizing_price/ | NikIta_Gx | self.LocalLLaMA | 1970-01-01T00:00:00 | 0 | {} | 1i3mi6e | false | null | t3_1i3mi6e | /r/LocalLLaMA/comments/1i3mi6e/a_local_model_recognizing_price/ | false | false | self | 1 | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.