lora-instruct
Roy
| lora-instruct | Roy | |
|---|---|---|
| 1 | 1 | |
| 97 | 66 | |
| - | - | |
| 7.0 | 8.0 | |
| 5 months ago | 7 months ago | |
| Python | Jupyter Notebook | |
| Apache License 2.0 | - |
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lora-instruct
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Training a LoRA with MPT Models
Hi, i have created custom data, same format as alphachas json file. And fine tuned mpt-7b-instruct using this link https://github.com/leehanchung/lora-instruct I have also used your patch, the fine tuning got successfull and also the loss got decreased but when am trying to make prediction using the fine tuned model am not getting correct output even on the trained data, it's generating output with lots of nonsense
Roy
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My take on Microsoft's `autogen` for multi-agent chat: `Roy`
So, I spent the weekend putting together Roy. I tried to replicate some of its features but in what I hoped would be a simpler, more straightforward way.
What are some alternatives?
FastLoRAChat - Instruct-tune LLaMA on consumer hardware with shareGPT data
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
AutoLearn-GPT - ChatGPT learns automatically.
SolidGPT - Developer AI Persona Search Agent
LMOps - General technology for enabling AI capabilities w/ LLMs and MLLMs
hngpt - Collecting my favoritet Hacker News stories by LangChain
mpt-lora-patch - Patch for MPT-7B which allows using and training a LoRA
gptq_for_langchain - A guide about how to use GPTQ models with langchain
punica - Serving multiple LoRA finetuned LLM as one
Local-LLM-Langchain - Load local LLMs effortlessly in a Jupyter notebook for testing purposes alongside Langchain or other agents. Contains Oobagooga and KoboldAI versions of the langchain notebooks with examples.
GPT-Agent - 🚀 Introducing 🐪 CAMEL: a game-changing role-playing approach for LLMs and auto-agents like BabyAGI & AutoGPT! Watch two agents 🤝 collaborate and solve tasks together, unlocking endless possibilities in #ConversationalAI, 🎮 gaming, 📚 education, and more! 🔥
ProTaska-GPT - Unleash the Potential of Datasets with Intelligent Tasks, Tutorials, and Algorithm Recommendations.