Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use anth0nyhak1m/PFPC_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anth0nyhak1m/PFPC_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anth0nyhak1m/PFPC_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anth0nyhak1m/PFPC_model") model = AutoModelForSequenceClassification.from_pretrained("anth0nyhak1m/PFPC_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbfc5a98d8abb5526fe60cdb71b6bcaa355191c05fa38a3bb5f591c8ca2b75ae
- Size of remote file:
- 3.58 kB
- SHA256:
- ebfe096f0f93bb25c5044cc3aff5282730ccb2fc2053af1a447a7de8a3c52f17
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