Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Gautamo1/my_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gautamo1/my_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gautamo1/my_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gautamo1/my_model") model = AutoModelForSequenceClassification.from_pretrained("Gautamo1/my_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85ef1b2292e646f06e2b221a9a225dcbae0be8ca9d6cfc0e5dd7b59af413f40b
- Size of remote file:
- 5.84 kB
- SHA256:
- 93020e3568955b2700b8fd0bb0e5f1debd9ff8fb87b0cabf487d682edc7da1c3
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