Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use quant-chef/trial-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quant-chef/trial-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="quant-chef/trial-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("quant-chef/trial-model") model = AutoModelForSequenceClassification.from_pretrained("quant-chef/trial-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7054a0932c0fdbc7b37db4fd24ebae7cf2aa0942a8f467d43dd80fd8f96197ad
- Size of remote file:
- 499 MB
- SHA256:
- c1da57788614d2ead67906c5a23ba5ba0898146c10d1d898c11a99e4278185e2
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