Instructions to use Noodle-bg/ccode-llama-instruct-7b-Python_assistant-Sft2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Noodle-bg/ccode-llama-instruct-7b-Python_assistant-Sft2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-Instruct-hf") model = PeftModel.from_pretrained(base_model, "Noodle-bg/ccode-llama-instruct-7b-Python_assistant-Sft2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Noodle-bg/ccode-llama-instruct-7b-Python_assistant-Sft2: direct link, hf CLI and curl.
- Browser
- Download file 4.79 kB
-
https://huggingface.co/Noodle-bg/ccode-llama-instruct-7b-Python_assistant-Sft2/resolve/main/training_args.bin
- Command line
-
hf download hf://Noodle-bg/ccode-llama-instruct-7b-Python_assistant-Sft2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Noodle-bg/ccode-llama-instruct-7b-Python_assistant-Sft2/resolve/main/training_args.bin
4.79 kB
- Xet hash:
- 909197ad52f3414f28ac537602789a59414ddfa9ab550c52ae7199c6cccb467f
- Size of remote file:
- 4.79 kB
- SHA256:
- 4d528f1552567e766e4b5f94011874842ede23d0df37f07128b6e020a93adee6
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