Instructions to use dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/resolve/main/training_args.bin
- Command line
-
hf download hf://dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 14b465c2136998b7084978e6c05feb07f3643e89ddd3c1f355a17704c488b139
- Size of remote file:
- 6.84 kB
- SHA256:
- 635e7e6fc3b47df5bf41ce4591df2abe14c7af9b0d70935919139a9d9e0d31fd
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