Instructions to use YakovElm/Cross_Project_10_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_10_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_10_Classic_Cross_Entropy_Samples")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Cross_Project_10_Classic_Cross_Entropy_Samples") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Cross_Project_10_Classic_Cross_Entropy_Samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from YakovElm/Cross_Project_10_Classic_Cross_Entropy_Samples: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/Cross_Project_10_Classic_Cross_Entropy_Samples/resolve/main/tf_model.h5
- Command line
-
hf download hf://YakovElm/Cross_Project_10_Classic_Cross_Entropy_Samples/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/YakovElm/Cross_Project_10_Classic_Cross_Entropy_Samples/resolve/main/tf_model.h5
438 MB
- Xet hash:
- 9fce6044d410fa192a96c135e0a4e6b8827accf8ba62911913e4836841971cc7
- Size of remote file:
- 438 MB
- SHA256:
- 5138736d7405ae6bd58ad05e01949055f1efc974a9aa81b4457bb223d6a0864c
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