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:
- cceaf3805a7548da876bf929fbf971002249e07cd98071e88cb4c014cfa52b81
- Size of remote file:
- 46.6 MB
- SHA256:
- 78bacd979776c3ccc2a8405ba190da41af6108747bc5e2b98c9263e6dfd60d23
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