Instructions to use howard-hou/IACC-compressor-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use howard-hou/IACC-compressor-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="howard-hou/IACC-compressor-small", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("howard-hou/IACC-compressor-small", trust_remote_code=True) model = AutoModel.from_pretrained("howard-hou/IACC-compressor-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from howard-hou/IACC-compressor-small: direct link, hf CLI and curl.
- Browser
- Download file 16.8 MB
-
https://huggingface.co/howard-hou/IACC-compressor-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://howard-hou/IACC-compressor-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/howard-hou/IACC-compressor-small/resolve/main/tokenizer.json
16.8 MB
- Xet hash:
- 49e18c6e461254ed002e698e5d8be3557e3e3f69733f6eb9b410370981d7b82a
- Size of remote file:
- 16.8 MB
- SHA256:
- 20a46ac256746594ed7e1e3ef733b83fbc5a6f0922aa7480eda961743de080ef
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