Instructions to use YakovElm/IntelDAOS5Classic_Cross_entropy_Sample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/IntelDAOS5Classic_Cross_entropy_Sample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/IntelDAOS5Classic_Cross_entropy_Sample")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/IntelDAOS5Classic_Cross_entropy_Sample") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/IntelDAOS5Classic_Cross_entropy_Sample", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from YakovElm/IntelDAOS5Classic_Cross_entropy_Sample: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/IntelDAOS5Classic_Cross_entropy_Sample/resolve/main/tf_model.h5
- Command line
-
hf download hf://YakovElm/IntelDAOS5Classic_Cross_entropy_Sample/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/YakovElm/IntelDAOS5Classic_Cross_entropy_Sample/resolve/main/tf_model.h5
438 MB
- Xet hash:
- 387ddbda03497f3d0833c559f1e3d1e8de57d76cb5fdcf98a79073abd6f227f7
- Size of remote file:
- 438 MB
- SHA256:
- d8d372afb902611d95c74b572b7f6dcd9d6d107b8e817c18a78ef9f3424486d8
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