Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use anth0nyhak1m/FPC_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anth0nyhak1m/FPC_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anth0nyhak1m/FPC_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anth0nyhak1m/FPC_model") model = AutoModelForSequenceClassification.from_pretrained("anth0nyhak1m/FPC_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 540128ac3ecc54f38f3c71c4392b16b607ddee714b00fe765eb6f950ce3f16d5
- Size of remote file:
- 268 MB
- SHA256:
- 33ffcaa85b3a21fa93a725b1269e083702e6062387939aeb10a04764a3c788a2
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