Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use platzi/NLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use platzi/NLP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="platzi/NLP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("platzi/NLP") model = AutoModelForSequenceClassification.from_pretrained("platzi/NLP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bdff744af92f4fde904c07c4948f12c4bc7208a694339efb263a921508dc82a3
- Size of remote file:
- 4.79 kB
- SHA256:
- 6c46d04648b0db066f7acfea0f009fabfb00a4f5c274c5e273fd20f0bd43b95f
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