Instructions to use devrunner09/classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devrunner09/classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="devrunner09/classification-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("devrunner09/classification-model") model = AutoModel.from_pretrained("devrunner09/classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from devrunner09/classification-model: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/devrunner09/classification-model/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://devrunner09/classification-model@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/devrunner09/classification-model/resolve/refs%2Fpr%2F1/model.safetensors
1.11 GB
- Xet hash:
- 2ee563c62b5310679ce4af926c203134f4a6fa2a3a948826705fa7e60c2d62b1
- Size of remote file:
- 1.11 GB
- SHA256:
- f5b02dac73d88601cb20ee9abb77a227b65fbfb9c3527a2942abe047ee8d34c0
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