Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Kimata/roberta-raw-text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kimata/roberta-raw-text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kimata/roberta-raw-text")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kimata/roberta-raw-text") model = AutoModelForSequenceClassification.from_pretrained("Kimata/roberta-raw-text", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 326011c59b5002732d2b6d34d7b0d5b09af8dd4f805a150ddbb91a2024e217fb
- Size of remote file:
- 5.37 kB
- SHA256:
- db734d512af3dd6e22ddc58b5796605c4b5772d6477d7c0868a2232a206e8db3
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