Instructions to use MENG21/studfacultyeval-BERT-BASE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MENG21/studfacultyeval-BERT-BASE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MENG21/studfacultyeval-BERT-BASE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MENG21/studfacultyeval-BERT-BASE") model = AutoModelForSequenceClassification.from_pretrained("MENG21/studfacultyeval-BERT-BASE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from MENG21/studfacultyeval-BERT-BASE: direct link, hf CLI and curl.
- Browser
- Download file 108 Bytes
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https://huggingface.co/MENG21/studfacultyeval-BERT-BASE/resolve/main/.gitattributes
- Command line
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hf download hf://MENG21/studfacultyeval-BERT-BASE/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/MENG21/studfacultyeval-BERT-BASE/resolve/main/.gitattributes
108 Bytes
| model.safetensors filter=lfs diff=lfs merge=lfs -text | |
| pytorch_model.bin filter=lfs diff=lfs merge=lfs -text | |