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 pytorch_model.bin from tanoManzo/MiniLM-attitude: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/tanoManzo/MiniLM-attitude/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tanoManzo/MiniLM-attitude/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tanoManzo/MiniLM-attitude/resolve/main/pytorch_model.bin
134 MB
- Xet hash:
- d8ed1cb5914be69a65675531d8b1a930879da66e2aa464313788495175a96a09
- Size of remote file:
- 134 MB
- SHA256:
- 87c06e368904a77861a27eed52af0ecd1599dfe0e6b15c8f213c8f72cb843aa2
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