Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mp6kv/paper_feedback_intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mp6kv/paper_feedback_intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mp6kv/paper_feedback_intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mp6kv/paper_feedback_intent") model = AutoModelForSequenceClassification.from_pretrained("mp6kv/paper_feedback_intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03e956ec6957586e3318aa2c3cd0453b5ad66c7a2b6fc3743e332662691e262e
- Size of remote file:
- 2.99 kB
- SHA256:
- 16a2f887018ad0d10ec06a635b2b440ee5219778bf0f5e290f43be0ff44aaaf8
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