Instructions to use ajtaltarabukin2022/cd66053e-4ef0-447b-af7f-d9e2f1fd43d5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ajtaltarabukin2022/cd66053e-4ef0-447b-af7f-d9e2f1fd43d5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-instruct-v0.2") model = PeftModel.from_pretrained(base_model, "ajtaltarabukin2022/cd66053e-4ef0-447b-af7f-d9e2f1fd43d5") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ajtaltarabukin2022/cd66053e-4ef0-447b-af7f-d9e2f1fd43d5: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/ajtaltarabukin2022/cd66053e-4ef0-447b-af7f-d9e2f1fd43d5/resolve/main/training_args.bin
- Command line
-
hf download hf://ajtaltarabukin2022/cd66053e-4ef0-447b-af7f-d9e2f1fd43d5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ajtaltarabukin2022/cd66053e-4ef0-447b-af7f-d9e2f1fd43d5/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- 374cb6b6ffcaa18b582c70fb1530a67a1f93ab17a60330cf26f69d87c2e234ee
- Size of remote file:
- 6.78 kB
- SHA256:
- 203d4d67f947b7b765597dbc99da149eba5e0a70706b0a70da8aeb59eca7cafc
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