Instructions to use hung200504/2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/2 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="hung200504/2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/2") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hung200504/2: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/hung200504/2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hung200504/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hung200504/2/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 3436d6bfb747687917c0dd3999723161e25a7b0df35f6245a7186f969f3f8eaa
- Size of remote file:
- 431 MB
- SHA256:
- 31bd718deec2ad96716f15395b1e9df3d74f8783fb07f939a0342634026a7a08
路
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