Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use hucruz/nmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hucruz/nmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hucruz/nmp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hucruz/nmp") model = AutoModelForSequenceClassification.from_pretrained("hucruz/nmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05ca1a46d0dc76b5c698e3c3aceb78722bc9e59286fc814f0259aadb1dee4815
- Size of remote file:
- 3.45 kB
- SHA256:
- eb93b1f9b6a7fccd6f7c1d7aa9349492c1a55508a014af36fe42b4c0c2eb8b6a
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