Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Manishkalra/discourse_classification_using_robrta_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manishkalra/discourse_classification_using_robrta_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Manishkalra/discourse_classification_using_robrta_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Manishkalra/discourse_classification_using_robrta_base") model = AutoModelForSequenceClassification.from_pretrained("Manishkalra/discourse_classification_using_robrta_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Manishkalra/discourse_classification_using_robrta_base: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/Manishkalra/discourse_classification_using_robrta_base/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Manishkalra/discourse_classification_using_robrta_base@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Manishkalra/discourse_classification_using_robrta_base/resolve/refs%2Fpr%2F1/training_args.bin
3.38 kB
- Xet hash:
- 997bbc08ee676aa75b4a4c6aa62a725b47888ca346bb79e77e9d73d6a746dde6
- Size of remote file:
- 3.38 kB
- SHA256:
- 4e281287b0dccdaf3c3f759c26098c8bb4abba8de9ca12456454b1356638d4fd
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