Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use AnonymousCS/temp_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/temp_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/temp_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/temp_model") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/temp_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1b9beffbd6ee8f980d8d5379359448c3ea098cd158d9257e906683c1a784331
- Size of remote file:
- 711 MB
- SHA256:
- f002e23c4c96ccccd4c4a437675e315c3f7c34c991fc9b3c4e255c2228b27fe4
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