WizardLM
chat-ui
WizardLM | chat-ui | |
---|---|---|
38 | 40 | |
7,531 | 6,314 | |
- | 10.0% | |
9.4 | 9.7 | |
8 months ago | 5 days ago | |
Python | TypeScript | |
- | Apache License 2.0 |
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WizardLM
- FLaNK AI-April 22, 2024
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Refact LLM: New 1.6B code model reaches 32% HumanEval and is SOTA for the size
This is interesting work, and a good contribution, but there is no need to mislead people.
[1] https://github.com/nlpxucan/WizardLM
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Continue with LocalAI: An alternative to GitHub's Copilot that runs everything locally
If you pair this with the latest WizardCoder models, which have a fairly better performance than the standard Salesforce Codegen2 and Codegen2.5, you have a pretty solid alternative to GitHub Copilot that runs completely locally.
- WizardCoder context?
- The world's most-powerful AI model suddenly got 'lazier' and 'dumber.' A radical redesign of OpenAI's GPT-4 could be behind the decline in performance.
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Official WizardLM-13B-V1.1 Released! Train with Only 1K Data! Can Achieve 86.32% on AlpacaEval!
(We will update the demo links in our github.)
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GPT-4 API general availability
In terms of speed, we're talking about 140t/s for 7B models, and 40t/s for 33B models on a 3090/4090 now.[1] (1 token ~= 0.75 word) It's quite zippy. llama.cpp performs close on Nvidia GPUs now (but they don't have a handy chart) and you can get decent performance on 13B models on M1/M2 Macs.
You can take a look at a list of evals here: https://llm-tracker.info/books/evals/page/list-of-evals - for general usage, I think home-rolled evals like llm-jeopardy [2] and local-llm-comparison [3] by hobbyists are more useful than most of the benchmark rankings.
That being said, personally I mostly use GPT-4 for code assistance to that's what I'm most interested in, and the latest code assistants are scoring quite well: https://github.com/abacaj/code-eval - a recent replit-3b fine tune the human-eval results for open models (as a point of reference, GPT-3.5 gets 60.4 on pass@1 and 68.9 on pass@10 [4]) - I've only just started playing around with it since replit model tooling is not as good as llamas (doc here: https://llm-tracker.info/books/howto-guides/page/replit-mode...).
I'm interested in potentially applying reflexion or some of the other techniques that have been tried to even further increase coding abilities. (InterCode in particular has caught my eye https://intercode-benchmark.github.io/)
[1] https://github.com/turboderp/exllama#results-so-far
[2] https://github.com/aigoopy/llm-jeopardy
[3] https://github.com/Troyanovsky/Local-LLM-comparison/tree/mai...
[4] https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder
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WizardLM-13B-V1.0-Uncensored
You talking about this? https://github.com/nlpxucan/WizardLM
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What 7b llm to use
The smallest model that is close to competent at code is WizardCoder 15B.. https://github.com/nlpxucan/WizardLM/
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16-Jun-2023
WizardCoder: Empowering Code Large Language Models with Evol-Instruct (https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder)
chat-ui
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Zephyr 141B, a Mixtral 8x22B fine-tune, is now available in Hugging Chat
Zephyr 141B is a Mixtral 8x22B fine-tune. Here are some interesting details
- Base model: Mixtral 8x22B, 8 experts, 141B total params, 35B activated params
- Fine-tuned with ORPO, a new alignment algorithm with no SFT step (hence much faster than DPO/PPO)
- Trained with 7K open data instances -> high-quality, synthetic, multi-turn
- Apache 2
Everything is open:
- Final Model: https://huggingface.co/HuggingFaceH4/zephyr-orpo-141b-A35b-v...
- Base Model: https://huggingface.co/mistral-community/Mixtral-8x22B-v0.1
- Fine-tune data: https://huggingface.co/datasets/argilla/distilabel-capybara-...
- Recipe/code to train the model: https://huggingface.co/datasets/argilla/distilabel-capybara-...
- Open-source inference engine: https://github.com/huggingface/text-generation-inference
- Open-source UI code https://github.com/huggingface/chat-ui
Have fun!
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AI enthusiasm - episode #2🚀
As long as you have a free Hugging Face account, you can sign up and exploit HuggingChat, a web-based chat interface where you will find 5 large language models to play with (Mixtral-7B-it v0.1 and v0.2, Command R plus, Gemma 1.1-7B-it, Dolphin). You will also have the possibility to exploit several assistants made by the Hugging Face community, or even create your own!
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OpenAI Startup Fund: GP Hallucination
I submitted something about this the other day (and it got flagged)- poked around a little bit and the only interesting thing I could find is this: https://github.com/huggingface/chat-ui/issues/254 and I don't really even understand what it is, it references the stuff the dude who wrote this is discussing. I had kinda written the whole thing off as someone with too much time on their hands and is just f'ing around with stuff for whatever reason.
I think they made this as well: https://chat.openai.com/g/g-KT4gusP3Y-a-l-i-s-t-a-i-r-e-earl... - it doesn't seem very useful.
*¯\_(ツ)_/¯ to me after spending an hr or so poking around, it seemed like a bored modern tech savvy young person playing around.
- ⚔️ Embeddings, Chatbots RAG Arena et forfaits Telecom OPT-NC
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Show HN: I made an app to use local AI as daily driver
- https://github.com/huggingface/chat-ui
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Deconstructing Hugging Face Chat: Explore open-source chat UI/UX for generative AI
Hugging Face Chat - open-source repo powering Hugging Chat!
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What are you guys using local LLMs for?
If you don't want to do coding, I think HuggingFace's chat-ui can come in handy with web retrieval RAG and llama-cpp running as a server. Please check their documentation on how to setup( See "Running your own models using a custom endpoint" section on their Github).
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The founder of OpenAI/ChatGPT is a Zionist calling people that are against Israeli genocide “antisemitist”, how dare the American left speak against genocide!?
yes! it's proprietary, invasive, and harvests your data and use it for improving the AI, Ultman went to Israel weeks after Chatgpt was introduced, Israel like any other tech-giant-country needs to make sure that it has control over that data and/or use it to achieve its goals, so it's better to find offline FOSS alternatives (if you have a decent enough PC) or use HuggingChat as an online FOSS alternative, I find it better than GPT 3.5 in many aspects
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Smartphone Brands Sorted Out, So You Don't Have To
I have categorized some of the smartphone brands by their parent company using HuggingChat based on RLHF, Google's Bard, ChatGPT, and Perplexity. All of them are powered by LLMs, and both ChatGPT and Perplexity use GPT-3.5.
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Accessing ChatGPT in non-official UI
I'm looking for something like https://huggingface.co/chat/ or OpenAssistant, but it should target OpenAI's api.
What are some alternatives?
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
promptfoo - Test your prompts, models, and RAGs. Catch regressions and improve prompt quality. LLM evals for OpenAI, Azure, Anthropic, Gemini, Mistral, Llama, Bedrock, Ollama, and other local & private models with CI/CD integration.
llm-humaneval-benchmarks
DiscordChatExporter-frontend - Browse json files exported by Tyrrrz/DiscordChatExporter in familiar discord like user interface
exllama - A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
basaran - Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
airoboros - Customizable implementation of the self-instruct paper.
Open-Assistant - OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
AgileRL - Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
can-ai-code - Self-evaluating interview for AI coders
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.