Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use tinutmap/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tinutmap/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tinutmap/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tinutmap/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("tinutmap/my_awesome_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d74a9778971c4fc56325ee97245d19edd404101b518146538d931fac45063649
- Size of remote file:
- 5.11 kB
- SHA256:
- c1236b5a2d9fca19029d95b73b0bc9a2842be738a54c1a3c867c7c0be8eb6bba
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