Instructions to use Cameron/BERT-rtgender-opgender-annotations with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-rtgender-opgender-annotations with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-rtgender-opgender-annotations")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-rtgender-opgender-annotations") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-rtgender-opgender-annotations", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Cameron/BERT-rtgender-opgender-annotations: direct link, hf CLI and curl.
- Browser
- Download file 867 MB
-
https://huggingface.co/Cameron/BERT-rtgender-opgender-annotations/resolve/main/optimizer.pt
- Command line
-
hf download hf://Cameron/BERT-rtgender-opgender-annotations/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Cameron/BERT-rtgender-opgender-annotations/resolve/main/optimizer.pt
867 MB
- Xet hash:
- f618ea5256eabf468390a61306873ec3fe6a12c88ba6e8dc522c44489036e439
- Size of remote file:
- 867 MB
- SHA256:
- 3b147b8c151bac4053c544dfe9276315b15be6ec44c070b5c0cdc96892ccbe63
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