Instructions to use Shenzy/Sentence_Classification4DesignTutor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shenzy/Sentence_Classification4DesignTutor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shenzy/Sentence_Classification4DesignTutor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shenzy/Sentence_Classification4DesignTutor") model = AutoModelForSequenceClassification.from_pretrained("Shenzy/Sentence_Classification4DesignTutor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Shenzy/Sentence_Classification4DesignTutor: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/Shenzy/Sentence_Classification4DesignTutor/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Shenzy/Sentence_Classification4DesignTutor/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Shenzy/Sentence_Classification4DesignTutor/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- a17047d651ebfd13f9a812ec26210a667f907306df931e12004a97d672f108c7
- Size of remote file:
- 1.42 GB
- SHA256:
- bd02da39aaae018d2eb21f1df5293f7397043f927bf3317f0e9ecfbf0eacbabc
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