Instructions to use isaaclee/mistral_train_seq_cls_run4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use isaaclee/mistral_train_seq_cls_run4 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "isaaclee/mistral_train_seq_cls_run4") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from isaaclee/mistral_train_seq_cls_run4: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/isaaclee/mistral_train_seq_cls_run4/resolve/main/training_args.bin
- Command line
-
hf download hf://isaaclee/mistral_train_seq_cls_run4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/isaaclee/mistral_train_seq_cls_run4/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 0ee84b7da829b85389847384b8dcf77e04cc6ed748687c031418250976b09dea
- Size of remote file:
- 4.73 kB
- SHA256:
- 96a16cec9cebbd2a120cf9f9c39a9f16d890ff6043524b27047bd8625e106c57
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.