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 adapter_model.safetensors from leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0: direct link, hf CLI and curl.
- Browser
- Download file 109 MB
-
https://huggingface.co/leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/leap-llm/Meta-Llama-3-8B-Instruct-sft-intercode-python-iter0/resolve/main/adapter_model.safetensors
109 MB
- Xet hash:
- d80546470b655466b44836fb79832c92c8b6cbe1db2db6b0a214b9e288a50bc9
- Size of remote file:
- 109 MB
- SHA256:
- 20130fc236577fc74d10b9369c6f7c8dbb475406d2250859f76dcd5cde9ded85
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