Instructions to use YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2/resolve/main/tf_model.h5
- Command line
-
hf download hf://YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/YakovElm/IntelDAOS10Classic_Cross_entropy_Sample_2/resolve/main/tf_model.h5
438 MB
- Xet hash:
- 8535cfb9a6bddbea7cdb6318e0737040e4354271d856f543cceb02efcd70ce81
- Size of remote file:
- 438 MB
- SHA256:
- f3a1f5a81c9b847802a630c38cefd6ac11c5f5ed57cbcd8aac8e56006fde90d1
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