Instructions to use Rodo-Sami/09604079-ea96-4397-98de-10d6884f5abb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Rodo-Sami/09604079-ea96-4397-98de-10d6884f5abb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceM4/tiny-random-LlamaForCausalLM") model = PeftModel.from_pretrained(base_model, "Rodo-Sami/09604079-ea96-4397-98de-10d6884f5abb") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Rodo-Sami/09604079-ea96-4397-98de-10d6884f5abb: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/Rodo-Sami/09604079-ea96-4397-98de-10d6884f5abb/resolve/7c35291bb79b4124ac6dbb3a0b9e4948db9f9ce4/training_args.bin
- Command line
-
hf download hf://Rodo-Sami/09604079-ea96-4397-98de-10d6884f5abb@7c35291bb79b4124ac6dbb3a0b9e4948db9f9ce4/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Rodo-Sami/09604079-ea96-4397-98de-10d6884f5abb/resolve/7c35291bb79b4124ac6dbb3a0b9e4948db9f9ce4/training_args.bin
6.78 kB
- Xet hash:
- f5f47a3a4b5398d365959ee0e03c394ec60508e905370bae65103d502919184e
- Size of remote file:
- 6.78 kB
- SHA256:
- f089b427fddc2e5f25d33c677aa6064384d1f4af4d3f3e62f019cbf8e335af28
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