Instructions to use Jose-Ribeir/second_try with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jose-Ribeir/second_try with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Jose-Ribeir/second_try")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Jose-Ribeir/second_try") model = AutoModelForQuestionAnswering.from_pretrained("Jose-Ribeir/second_try", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jose-Ribeir/second_try: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/Jose-Ribeir/second_try/resolve/main/training_args.bin
- Command line
-
hf download hf://Jose-Ribeir/second_try/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jose-Ribeir/second_try/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 011251d60b2a6c0842c51f98edc7ef6d854fd3cb83ea91bf2f6c6e7c8c5b083e
- Size of remote file:
- 5.05 kB
- SHA256:
- b755ff7fd5d49aa7b384ac47f5fa02648a93111fd987014669c8e034b0a46b95
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