Instructions to use vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen 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 vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen 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 vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-yahma-then-quizgen", max_seq_length=2048, )
- Xet hash:
- 2f60f4de944c200457ccff93dc97f0783ea1de2a61a0098747dd996152e07e3e
- Size of remote file:
- 45.1 MB
- SHA256:
- 08fcabb3acaa8c2dc0676c0c6bb0f2a4b51cfcd154ed984710012127f8968c67
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