Instructions to use antimage88/5e38fa20-914c-4a73-ac8b-091808a017c8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use antimage88/5e38fa20-914c-4a73-ac8b-091808a017c8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jhflow/mistral7b-lora-multi-turn-v2") model = PeftModel.from_pretrained(base_model, "antimage88/5e38fa20-914c-4a73-ac8b-091808a017c8") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from antimage88/5e38fa20-914c-4a73-ac8b-091808a017c8: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/antimage88/5e38fa20-914c-4a73-ac8b-091808a017c8/resolve/main/training_args.bin
- Command line
-
hf download hf://antimage88/5e38fa20-914c-4a73-ac8b-091808a017c8/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/antimage88/5e38fa20-914c-4a73-ac8b-091808a017c8/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 40d34c6b64b163f757b8c9b463aba87f405324cb6e0d20f4b938c0e38b15ed50
- Size of remote file:
- 6.78 kB
- SHA256:
- 248d26c379243ddb463a994847fd3a14f868b0a553e6a6647812889215647b30
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.