Text Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use RawMean/model_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RawMean/model_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RawMean/model_dir")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RawMean/model_dir") model = AutoModelForSequenceClassification.from_pretrained("RawMean/model_dir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from RawMean/model_dir: direct link, hf CLI and curl.
- Browser
- Download file 568 MB
-
https://huggingface.co/RawMean/model_dir/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://RawMean/model_dir/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RawMean/model_dir/resolve/main/pytorch_model.bin
568 MB
- Xet hash:
- 0f3aac3387c9ebaba4a0f252c0bb1e0ce8b72de26029739296c3117cb6badbf3
- Size of remote file:
- 568 MB
- SHA256:
- c5cc4236c3d531e2e61347e06b57ebcc824e27c5439156d938c0813c8e509583
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