Text Classification
Transformers
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
Instructions to use grexit-d/multipride_umberto_sent_label with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use grexit-d/multipride_umberto_sent_label with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="grexit-d/multipride_umberto_sent_label")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("grexit-d/multipride_umberto_sent_label") model = AutoModelForSequenceClassification.from_pretrained("grexit-d/multipride_umberto_sent_label") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1eb961315b6a7c876fda8e8e6af91d9bb8dbbf28bd820d81e1f894cea5ae45f
- Size of remote file:
- 5.84 kB
- SHA256:
- e4a787f99e2ad99b0835d48212daa46b37782a89430fa21f09606fcc970d8327
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