Instructions to use Kdogs/Capstone_IT_BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kdogs/Capstone_IT_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_IT_BERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Kdogs/Capstone_IT_BERT") model = AutoModelForQuestionAnswering.from_pretrained("Kdogs/Capstone_IT_BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Kdogs/Capstone_IT_BERT: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/Kdogs/Capstone_IT_BERT/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Kdogs/Capstone_IT_BERT/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Kdogs/Capstone_IT_BERT/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 831ca027c9e2f99b71f1fe70dc2bff969c4be6843a9f09e338e951964aa11dc4
- Size of remote file:
- 440 MB
- SHA256:
- 38a0e2cd46b24c2601251f2dfa55d57a401f77c67d8d1fff232282bce2f2ac47
路
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