Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use edloginovad/tinybert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edloginovad/tinybert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edloginovad/tinybert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edloginovad/tinybert") model = AutoModelForSequenceClassification.from_pretrained("edloginovad/tinybert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6216668c607f841d2ed914f640300034474c41738ffa77eb641cda1c87e509b5
- Size of remote file:
- 5.24 kB
- SHA256:
- 0552f03a15fb8e478ae25c7f694517e167b1c90d3a3434f8f135e254a9a40599
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