Instructions to use hamayo/llm-jp-3-13b-it_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamayo/llm-jp-3-13b-it_lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hamayo/llm-jp-3-13b-it_lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use hamayo/llm-jp-3-13b-it_lora with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for hamayo/llm-jp-3-13b-it_lora to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for hamayo/llm-jp-3-13b-it_lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hamayo/llm-jp-3-13b-it_lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="hamayo/llm-jp-3-13b-it_lora", max_seq_length=2048, )
Uploaded model
- Developed by: hamayo
- License: apache-2.0
- Finetuned from model : llm-jp/llm-jp-3-13b
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
概要:llm-jp \llmーjp-3-13bをunslothを使って4bit量子化したモデルです。 松尾研大規模言語モデル講座2024のコンペ用の提出モデル作成の一環として作成・公開しています。 LLM-jp の公開している Ichikara Instruction を用いてSFTしています。 ELYZA-tasks-100-TVを読み込み、llm-jp-3-13b-it-output.jsonlを出力しています。
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llm-jp/llm-jp-3-13b