Instructions to use hurtmongoose/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hurtmongoose/results with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small") model = PeftModel.from_pretrained(base_model, "hurtmongoose/results") - Transformers
How to use hurtmongoose/results with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hurtmongoose/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from hurtmongoose/results: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/hurtmongoose/results/resolve/main/training_args.bin
- Command line
-
hf download hf://hurtmongoose/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/hurtmongoose/results/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- 07226a9013577cd366ff8d53f653cfaf569eb08739c3f527ecda6daf8d344590
- Size of remote file:
- 5.91 kB
- SHA256:
- 37732dfaac4bc48f6279721bddc1c8aa290591031a7af5603debbfdbfc20b3f0
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