Instructions to use leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0/resolve/main/tokenizer.json
- Command line
-
hf download hf://leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0/resolve/main/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.