Text Classification
Transformers
TensorFlow
roberta
generated_from_keras_callback
text-embeddings-inference
Instructions to use Drigoro/roberta_original with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Drigoro/roberta_original with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Drigoro/roberta_original")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Drigoro/roberta_original") model = AutoModelForSequenceClassification.from_pretrained("Drigoro/roberta_original", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from Drigoro/roberta_original: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Drigoro/roberta_original/resolve/main/tf_model.h5
- Command line
-
hf download hf://Drigoro/roberta_original/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Drigoro/roberta_original/resolve/main/tf_model.h5
499 MB
- Xet hash:
- b0af8391e83e77a583f0b7317a22e5b3a50577759127ab580213310675146204
- Size of remote file:
- 499 MB
- SHA256:
- c1644c9a4d8dc895b612d19b55f0dde031a78a74130a8ba155cd9d20eee586a9
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