Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use javdrher/classifiertest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use javdrher/classifiertest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="javdrher/classifiertest")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("javdrher/classifiertest") model = AutoModelForSequenceClassification.from_pretrained("javdrher/classifiertest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 652abcb700547cd739c63397e107fde13ab2e79dfe70c89c91be9389bd803e61
- Size of remote file:
- 5.84 kB
- SHA256:
- 7fc8b49b04410bdff6a3bc50c4a1f3b9f76e42cb55e7df2dd16014d8ece2602b
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