Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use cristian-rivera/npl-transformes-crivera with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cristian-rivera/npl-transformes-crivera with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cristian-rivera/npl-transformes-crivera")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cristian-rivera/npl-transformes-crivera") model = AutoModelForSequenceClassification.from_pretrained("cristian-rivera/npl-transformes-crivera", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a3707f6f74e3bfd8312d15602cd21639c1fda095fc245b92ac1d34a9e49a5d9
- Size of remote file:
- 5.3 kB
- SHA256:
- 5272ef8f1c9ac758a4e57e8c7802afe998e10dfc59b845631e4cc7acc56eb734
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