Instructions to use Kdogs/Capstone_SPORTS_BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kdogs/Capstone_SPORTS_BERT 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="Kdogs/Capstone_SPORTS_BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Kdogs/Capstone_SPORTS_BERT") model = AutoModelForQuestionAnswering.from_pretrained("Kdogs/Capstone_SPORTS_BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Kdogs/Capstone_SPORTS_BERT: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/Kdogs/Capstone_SPORTS_BERT/resolve/main/training_args.bin
- Command line
-
hf download hf://Kdogs/Capstone_SPORTS_BERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Kdogs/Capstone_SPORTS_BERT/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- bb993f2cd48cf9cb32f7fd3cb7162c2e58df3ac56ae5b3cb530c403b519ca6d7
- Size of remote file:
- 3.64 kB
- SHA256:
- ef16f5ac9bf88cf108595308c417f6b4f20c918021f258c8c4a9e85a86ec51e2
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