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 flax_model.msgpack from khanh98/model3: direct link, hf CLI and curl.
- Browser
- Download file 540 MB
-
https://huggingface.co/khanh98/model3/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://khanh98/model3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/khanh98/model3/resolve/main/flax_model.msgpack
540 MB
- Xet hash:
- 83d55d7cc32f3de3edfe9ace927b24f4c44a8fac0f928018742fc553453ba49a
- Size of remote file:
- 540 MB
- SHA256:
- 05622b242748f0813827f1e013f9516e9c2d94825307e20bf6b2c85419dcabc0
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