can-ai-code
coronavirus
can-ai-code | coronavirus | |
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30 | 126 | |
471 | 1,095 | |
- | 0.0% | |
9.5 | 10.0 | |
9 days ago | over 3 years ago | |
Python | Python | |
MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
can-ai-code
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Ask HN: Code Llama 70B on a dedicated server
You can run a Q4 quant of a 70B model in about 40GB of RAM (+context). You're single user (batch size 1, bs=1) inference speed will be basically memory bottlenecked, so on a dual channel dedicated box you'd expect somewhere about 1 token/s. That's inference, prefill/prompt generation will take even longer (as your chat history grows) on CPU. So falls into the realm of technically possible, but not for real world use.
If you're looking specifically for CodeLlama 70B, Artificial Analysis https://artificialanalysis.ai/models/codellama-instruct-70b/... lists Perplexity, Together.ai, Deep Infra, and Fireworks as potential hosts, with Together.ai and Deepinfra at about $0.9/1M tokens, with about 30 tokens/s and about 300ms latency (time to first token).
For those looking for local coding models in specifically. I keep a list of LLM coding evals here: https://llm-tracker.info/evals/Code-Evaluation
On the EvalPlus Leaderboard, there about about 10 open models that rank higher than CodeLlama 70B, all smaller models: https://evalplus.github.io/leaderboard.html
A few other evals (worth cross-referencing to counter contamination, overfitting):
* CRUXEval Leaderboard https://crux-eval.github.io/leaderboard.html
* CanAiCode Leaderboard https://huggingface.co/spaces/mike-ravkine/can-ai-code-resul...
* Big Code Models Leaderboard https://huggingface.co/spaces/bigcode/bigcode-models-leaderb...
From the various leaderboards, deepseek-ai/deepseek-coder-33b-instruct still looks like the best performing open model (it has a very liberal ethical license), followed by ise-uiuc/Magicoder-S-DS-6.7B (a deepseek-coder-6.7b-base fine tune). The former can be run as a Q4 quant on a single 24GB GPU (a used 3090 should run you about $700 atm), and the latter, if it works for you will run 4X faster and fit on even cheaper/weaker GPUs.
There's always recent developments, but two worth pointing out:
OpenCodeInterpreter - a new system that uses execution feedback and outperforms ChatGPT4 Code Interpreter that is fine-tuned off of the DeepSeek code models: https://opencodeinterpreter.github.io/
StarCoder2-15B just dropped and also looks competitive. Announcement and relevant links: https://huggingface.co/blog/starcoder2
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Meta AI releases Code Llama 70B
This is a completely fair, but open question. Not to be a typical HN user, but when you say SOTA local, the question is really what benchmarks do you really care about in order to evaluate. Size, operability, complexity, explainability etc.
Working out what copilot models perform best has been a deep exercise for myself and has really made me evaluate my own coding style on what I find important and things I look out for when investigating models and evaluating interview candidates.
I think three benchmarks & leaderboards most go to are:
https://huggingface.co/spaces/bigcode/bigcode-models-leaderb... - which is the most understood, broad language capability leaderboad that relies on well understood evaluations and benchmarks.
https://huggingface.co/spaces/mike-ravkine/can-ai-code-resul... - Also comprehensive, but primarily assesses Python and JavaScript.
https://evalplus.github.io/leaderboard.html - which I think is a better take on comparing models you intend to run locally as you can evaluate performance, operability and size in one visualisation.
Best of luck and I would love to know which models & benchmarks you choose and why.
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Stable Code 3B: Coding on the Edge
Here is a leader board of some models
https://huggingface.co/spaces/mike-ravkine/can-ai-code-resul...
Don't know how biased this leaderboard is, but I guess you could just give some of them a try and see for yourself.
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Mistral has an even more powerfull model in the prototype-phase
- Can AI Code? - https://huggingface.co/spaces/mike-ravkine/can-ai-code-results
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Assessing llms for code generation.
Check out https://github.com/the-crypt-keeper/can-ai-code for some ideas. I'd love to see more shootouts like this. Especially if they were spread out among a few different languages.
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Show HN: LlamaGPT โ Self-hosted, offline, private AI chatbot, powered by Llama 2
Very cool, this looks like a combination of chatbot-ui and llama-cpp-python? A similar project I've been using is https://github.com/serge-chat/serge. Nous-Hermes-Llama2-13b is my daily driver and scores high on coding evaluations (https://huggingface.co/spaces/mike-ravkine/can-ai-code-resul...).
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How Is LLaMa.cpp Possible?
I have several sets of quant comparisons posted on my HF spaces, the caveat is my prompts are all "English to code": https://huggingface.co/spaces/mike-ravkine/can-ai-code-compa...
The dropdown at the top selects which comparison: Falcon compares GGML, Vicuna compares bits and bytes. I have some more comparisons planned, feel free to open an issue if you'd like to see something specific: https://github.com/the-crypt-keeper/can-ai-code
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Ask HN: Who is using small OS LLMs in production?
Yeah it seemed suspiciously high for HumanEval and it only ranks 14th for JS and 7th for Python on other benchmarks now: https://huggingface.co/spaces/mike-ravkine/can-ai-code-resul...
WizardCoder is a bit of a problem since it's not llama 1/2 based but is its own 15B model and as such the support for it in anything practical is near nonexistent. WizardLM v1.2 looks like it may be worth checking out.
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Recent updates on the LLM Explorer (15,000+ LLMs listed)
There are at least 4 different types of quants floating around HF (bitsandbytes, GGML, GPTQ and AWQ) so I dont know if a "GGML" column makes sense vs a more abstract way of linking quants to their base models. I am doing this and its fucking awful: https://github.com/the-crypt-keeper/can-ai-code/blob/main/models/models.yaml
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Did anyone try to benchmark LLM's for coding against each other and against proprietary ones like Copilot X?
Ah I meant this one but I see now it's WIP.
coronavirus
- Folding@Home: We empower anyone to become a citizen scientist
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Fly.it Has GPUs Now
How difficult world it be to set up Folding@home on these? https://foldingathome.org
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Ask HN: What fuel for my data furnace?
My personal recommendation would be Folding@Home[1]. Protein folding is an insanely complex thing life does and they use distributed computing to try to solve the large problems.
1. https://foldingathome.org/?lng=en
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UPDATED ๐เนัเนั เนเธะบัะณ contest 1.9k Banano to win! ๐ผ๐ฐ๐บ๐ด ๐
๐ท๐ธ๐
๐ผ๐ด๐ผ๐ด๐
Context: Banano team is the top contributor to Folding@Home which is a philanthropic project that uses computing power to help study complex proteins involved in disease research, seeking preventions and cures! https://bananominer.com/ https://foldingathome.org/
- If you got a very powerful GPU but don't use it for gaming. Then what do you use it for?
- Things to do with spare performance?
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The Banano daily jungle discussion
A major and essential part of the Banano culture is helping fight various diseases through the use of Folding at Home. You can join the team here at Banano miner and earn Banano whilst contributing to science. For almost two years Banano has been the top contributor other than the default team. For more information on this check out Folding at Home statistics.
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Making use of 32 gb RAM
foldingathome.org try this op
- Ask HN: Lots of AWS credits expiring soon, ideas?
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What would you do with 10-20 HP EliteDesks?
Others could be used for folding@home. If you want to try it
What are some alternatives?
llm-humaneval-benchmarks
bananovault - Open source wallet for using the Banano cryptocurrency
WizardLM - Family of instruction-following LLMs powered by Evol-Instruct: WizardLM, WizardCoder and WizardMath
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
kalium_wallet_flutter - Kalium Mobile BANANO Wallet, made with Flutter.
openchat - OpenChat: Advancing Open-source Language Models with Imperfect Data
idena-go - Idena node
Local-LLM-Comparison-Colab-UI - Compare the performance of different LLM that can be deployed locally on consumer hardware. Run yourself with Colab WebUI.
CurecoinSource - Curecoin 2.0+ Source Code
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
chunky - A path tracer to create realistic images of your Minecraft worlds.