Instructions to use LsTam/Llama-3.2-3B-Instruct_reference_text_st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LsTam/Llama-3.2-3B-Instruct_reference_text_st with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("LsTam/Llama-3.2-3B-Instruct_reference_text_st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from LsTam/Llama-3.2-3B-Instruct_reference_text_st: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/LsTam/Llama-3.2-3B-Instruct_reference_text_st/resolve/main/tokenizer.json
- Command line
-
hf download hf://LsTam/Llama-3.2-3B-Instruct_reference_text_st/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/LsTam/Llama-3.2-3B-Instruct_reference_text_st/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 09275f61ffb12918cdca254693e60b2b0689a20b6a0839cb38948af56246aaa2
- Size of remote file:
- 17.2 MB
- SHA256:
- 6bd80b3974c5165b8db1847b2bad25298ea8a170f02bc137155c5ce576adf759
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