Instructions to use YakovElm/IntelDAOS20Classic_Cross_entropy_Sample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/IntelDAOS20Classic_Cross_entropy_Sample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/IntelDAOS20Classic_Cross_entropy_Sample")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/IntelDAOS20Classic_Cross_entropy_Sample") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/IntelDAOS20Classic_Cross_entropy_Sample", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from YakovElm/IntelDAOS20Classic_Cross_entropy_Sample: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/IntelDAOS20Classic_Cross_entropy_Sample/resolve/main/tf_model.h5
- Command line
-
hf download hf://YakovElm/IntelDAOS20Classic_Cross_entropy_Sample/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/YakovElm/IntelDAOS20Classic_Cross_entropy_Sample/resolve/main/tf_model.h5
438 MB
- Xet hash:
- 8162bcb1831d1ab814fb066d1ae2ca41bd5c680064e644249d02e691ff4adc92
- Size of remote file:
- 438 MB
- SHA256:
- e754e66826ae2a5f0d64f8b672b01dcd0e0d0b89d697a2152d6694675069bc8a
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