Instructions to use wesley7137/MetaMath-CodeLlama-Python-7B-V1-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use wesley7137/MetaMath-CodeLlama-Python-7B-V1-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-Python-hf") model = PeftModel.from_pretrained(base_model, "wesley7137/MetaMath-CodeLlama-Python-7B-V1-lora") - Notebooks
- Google Colab
- Kaggle
Download rng_state.pth from wesley7137/MetaMath-CodeLlama-Python-7B-V1-lora: direct link, hf CLI and curl.
- Browser
- Download file 14.6 kB
-
https://huggingface.co/wesley7137/MetaMath-CodeLlama-Python-7B-V1-lora/resolve/main/rng_state.pth
- Command line
-
hf download hf://wesley7137/MetaMath-CodeLlama-Python-7B-V1-lora/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/wesley7137/MetaMath-CodeLlama-Python-7B-V1-lora/resolve/main/rng_state.pth
14.6 kB
- Xet hash:
- 91ec420618d0106de2bfc015d2e52afba583c131ef05e508044228e526f8dd88
- Size of remote file:
- 14.6 kB
- SHA256:
- ffaeedca22948b7fc77e859b2ec937650fb10a508455f9d6069ddbc5adefad13
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