Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use cedricbonhomme/tinyTinyModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cedricbonhomme/tinyTinyModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cedricbonhomme/tinyTinyModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cedricbonhomme/tinyTinyModel") model = AutoModelForSequenceClassification.from_pretrained("cedricbonhomme/tinyTinyModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from cedricbonhomme/tinyTinyModel: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/cedricbonhomme/tinyTinyModel/resolve/main/training_args.bin
- Command line
-
hf download hf://cedricbonhomme/tinyTinyModel/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/cedricbonhomme/tinyTinyModel/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 4d3a1b96f4aa3f902db5ab04cbcc888adb1b8a505420e6d0b4790031747582e7
- Size of remote file:
- 5.3 kB
- SHA256:
- 4c07b91ad19567905899d89e9f42f29f3cdb098cf1c4fc0e70d140e80086e582
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