Instructions to use khanh98/model3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khanh98/model3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="khanh98/model3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("khanh98/model3") model = AutoModelForSequenceClassification.from_pretrained("khanh98/model3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from khanh98/model3: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/khanh98/model3/resolve/main/tf_model.h5
- Command line
-
hf download hf://khanh98/model3/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/khanh98/model3/resolve/main/tf_model.h5
543 MB
- Xet hash:
- 48d48045d53a7eb0a54520fa18d99ba407107f76315204e8fc29073619f12b95
- Size of remote file:
- 543 MB
- SHA256:
- 780d243549ddcb75eb942d604488ac5ef2349ac908704ae7401bf579cb469812
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