Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use anth0nyhak1m/CFGFP_BasicTypeCalssifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anth0nyhak1m/CFGFP_BasicTypeCalssifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anth0nyhak1m/CFGFP_BasicTypeCalssifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anth0nyhak1m/CFGFP_BasicTypeCalssifier") model = AutoModelForSequenceClassification.from_pretrained("anth0nyhak1m/CFGFP_BasicTypeCalssifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f2b64c14b17a19b9259adab35d6680e85fbbd975ebe4d19d3617808fd3e2393
- Size of remote file:
- 270 MB
- SHA256:
- 860e85cf9dd2848c867f9feefe0ff6feacee93457b5595cdc79d897553709993
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