Instructions to use truong1301/vifactcheck_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use truong1301/vifactcheck_4 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="truong1301/vifactcheck_4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("truong1301/vifactcheck_4") model = AutoModelForQuestionAnswering.from_pretrained("truong1301/vifactcheck_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from truong1301/vifactcheck_4: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/truong1301/vifactcheck_4/resolve/main/tokenizer.json
- Command line
-
hf download hf://truong1301/vifactcheck_4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/truong1301/vifactcheck_4/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 0958cadcf97a8d8abb97f3112bbb68630f2b97c45009e0c133698457a1fe9c8c
- Size of remote file:
- 16.3 MB
- SHA256:
- d72f43cffd0dfbeb58d31a9bf13be33ac1c0d7c6691e09b6238d711cf11b6610
路
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