Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use anth0nyhak1m/CFGFP_BasicTypeCalssifier_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anth0nyhak1m/CFGFP_BasicTypeCalssifier_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anth0nyhak1m/CFGFP_BasicTypeCalssifier_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anth0nyhak1m/CFGFP_BasicTypeCalssifier_v1") model = AutoModelForSequenceClassification.from_pretrained("anth0nyhak1m/CFGFP_BasicTypeCalssifier_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cf3523714c4cf03b94e2b1f7e2abb1c327a4eb0df35e911cf33d85ed5cbbace
- Size of remote file:
- 3.64 kB
- SHA256:
- b23936efb1539693f95f6286ac906a00b6a2c8092c804f8dbbc9c3e56ab3ed1f
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