Instructions to use daspartho/subreddit-predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daspartho/subreddit-predictor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="daspartho/subreddit-predictor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("daspartho/subreddit-predictor") model = AutoModelForSequenceClassification.from_pretrained("daspartho/subreddit-predictor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from daspartho/subreddit-predictor: direct link, hf CLI and curl.
- Browser
- Download file 269 MB
-
https://huggingface.co/daspartho/subreddit-predictor/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://daspartho/subreddit-predictor/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/daspartho/subreddit-predictor/resolve/main/pytorch_model.bin
269 MB
- Xet hash:
- 06308075b8a09a5bbc53f81bd13585960ad8faf020b89a5b2a0d89f589833a91
- Size of remote file:
- 269 MB
- SHA256:
- de8f78a725399816633d142b0d63712e794030fa2d52c3516d3bfc04c944939b
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