Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Manishkalra/discourse_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Manishkalra/discourse_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Manishkalra/discourse_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Manishkalra/discourse_classification") model = AutoModelForSequenceClassification.from_pretrained("Manishkalra/discourse_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Manishkalra/discourse_classification: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/Manishkalra/discourse_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Manishkalra/discourse_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Manishkalra/discourse_classification/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 6a4023d97100a03fbba13e1a8e0456fee5ca8e54cac3f42ae774d93656b3ebc2
- Size of remote file:
- 3.31 kB
- SHA256:
- 8d5c3ac731f53ffbc9023e721b2deecf1a867281a3efcc62d1a43a725b3cc475
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