Instructions to use Mohamed1213/model_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Mohamed1213/model_checkpoints with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3") model = PeftModel.from_pretrained(base_model, "Mohamed1213/model_checkpoints") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mohamed1213/model_checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/Mohamed1213/model_checkpoints/resolve/main/training_args.bin
- Command line
-
hf download hf://Mohamed1213/model_checkpoints/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mohamed1213/model_checkpoints/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 11b65f2c6fa4950336d12e49d573e9db9535f4be8f5e6a2155f175ed662def9b
- Size of remote file:
- 5.43 kB
- SHA256:
- a3abd455b0b3cc3d54595b19af11726ff11a86be686863bf1a2f6aa4657f70b8
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