Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use userABC123/IA_MODEL_2e_WINNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use userABC123/IA_MODEL_2e_WINNER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="userABC123/IA_MODEL_2e_WINNER")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("userABC123/IA_MODEL_2e_WINNER") model = AutoModelForSequenceClassification.from_pretrained("userABC123/IA_MODEL_2e_WINNER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 661ad896f33aa8d7884becb0d8e70142060e01413287f81aa249f7fecb23cf32
- Size of remote file:
- 5.2 kB
- SHA256:
- 708b9c6b63d68e7858bba0230ac4ce8e3ae918b54dcbde6a4d13ef2ebadcb79c
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