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:
- f30a868e6b43588c394aa7865f4bf3d8a19532875e15ae7d918d87c56c877a8a
- Size of remote file:
- 3.58 kB
- SHA256:
- 139de3d3011db1c6f0b8a4af30c8f51e034f4b1dd279df22adfa719b0cd64bd3
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