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 model.safetensors from MENG21/studfacultyeval-BERT-BASE: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/MENG21/studfacultyeval-BERT-BASE/resolve/main/model.safetensors
- Command line
-
hf download hf://MENG21/studfacultyeval-BERT-BASE/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/MENG21/studfacultyeval-BERT-BASE/resolve/main/model.safetensors
438 MB
- Xet hash:
- 648ce868308cc4b2d18b1d14af8dbe11dbc40fa73513f1ff623a0878c97a18fa
- Size of remote file:
- 438 MB
- SHA256:
- a54c1b1032fe2ec3ae3da7b50f70583966595b61ab4fb39409c5c2f618f410df
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