Code and documentation to train Stanford's Alpaca models, and generate the data.
- deep-learning
- instruction-following
- language-model
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Code and documentation to train Stanford's Alpaca models, and generate the data.
TranslatedChinese LLaMA & Alpaca LLMs + local CPU/GPU training and deployment
Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU.
TranslatedChinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models
TranslatedFirefly: a large model training tool that supports training large models such as Qwen2.5, Qwen2, Yi1.5, Phi-3, Llama3, Gemma, MiniCPM, Yi, Deepseek, Orion, Xverse, Mixtral-8x7B, Zephyr, Mistral, Baichuan2, Llma2, Llama, Qwen, Baichuan, ChatGLM2, InternLM, Ziya2, Vicuna, Bloom, etc.
Open-source multimodal retrieval engine (Morphik Core)
Together Mixture-Of-Agents (MoA) – 65.1% on AlpacaEval with OSS models
The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.
Code and documents of LongLoRA and LongAlpaca (ICLR 2024 Oral)
mPLUG-Owl: The Powerful Multi-modal Large Language Model Family