Instructions to use tanoManzo/MiniLM-attitude with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanoManzo/MiniLM-attitude with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tanoManzo/MiniLM-attitude")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tanoManzo/MiniLM-attitude") model = AutoModelForSequenceClassification.from_pretrained("tanoManzo/MiniLM-attitude", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tanoManzo/MiniLM-attitude: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/tanoManzo/MiniLM-attitude/resolve/main/training_args.bin
- Command line
-
hf download hf://tanoManzo/MiniLM-attitude/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tanoManzo/MiniLM-attitude/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 0db949415afa9bc63072d5677bee6e5d738cbfbdafa4a4a937318cff1687916c
- Size of remote file:
- 3.52 kB
- SHA256:
- 04724cd3dfd3349931ce683cf02f80dedf2396b04c4af11893cedd1b080bc7de
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