Instructions to use YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples/resolve/main/tf_model.h5
- Command line
-
hf download hf://YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/YakovElm/Cross_Project_5_Classic_Cross_Entropy_Samples/resolve/main/tf_model.h5
438 MB
- Xet hash:
- 369b3b530b1c53b02c904a710e7c194ca4003df5c9edbcf21a6ccbf4cc6c2035
- Size of remote file:
- 438 MB
- SHA256:
- d05518ff30abc2add6aafbfef1abb31c64351790812585bde70b9d8c9ea1f4fb
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