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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 381d63e9833e3c1380aadc377c34be7ecb3efa390750553bf88c8d99e5b3690f
- Size of remote file:
- 5.3 kB
- SHA256:
- cdb141284f4649200f70f1f5aef43daedc104b3dbaab50115e1afeb41f6951fa
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