Instructions to use isaaclee/duration_mistral_train_run3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use isaaclee/duration_mistral_train_run3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained(base_model, "isaaclee/duration_mistral_train_run3") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from isaaclee/duration_mistral_train_run3: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/isaaclee/duration_mistral_train_run3/resolve/main/training_args.bin
- Command line
-
hf download hf://isaaclee/duration_mistral_train_run3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/isaaclee/duration_mistral_train_run3/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 6ccae0289007e006712efbdda614f89532a8205668dbf69d35fb510ddaddf821
- Size of remote file:
- 4.73 kB
- SHA256:
- 5c50cca55c51e0770129b4244802472aa0ea22fb8637fa9f905c9a2354833f8c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.