Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use liamvbetts/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liamvbetts/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="liamvbetts/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("liamvbetts/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("liamvbetts/my_awesome_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d08df1c3d32a4f6170a99f30db3e272bc3e90b0dde5af751a35fb9bf9cb2612
- Size of remote file:
- 17.1 MB
- SHA256:
- 8373f9cd3d27591e1924426bcc1c8799bc5a9affc4fc857982c5d66668dd1f41
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