Instructions to use isaaclee/duration_mistral_train_run2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use isaaclee/duration_mistral_train_run2 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_run2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from isaaclee/duration_mistral_train_run2: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/isaaclee/duration_mistral_train_run2/resolve/main/training_args.bin
- Command line
-
hf download hf://isaaclee/duration_mistral_train_run2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/isaaclee/duration_mistral_train_run2/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- a274141f3643dee7c18534d08b2f9f28f4c03048b33377f24ac131dd97cbe70e
- Size of remote file:
- 4.73 kB
- SHA256:
- c0689feb65ed2942ab421f572f7c75642c44e152568564729270129b40a8aa01
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.