Instructions to use APredator/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use APredator/results with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("APredator/results") model = AutoModelForSeq2SeqLM.from_pretrained("APredator/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from APredator/results: direct link, hf CLI and curl.
- Browser
- Download file 16.4 MB
-
https://huggingface.co/APredator/results/resolve/main/tokenizer.json
- Command line
-
hf download hf://APredator/results/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/APredator/results/resolve/main/tokenizer.json
16.4 MB
- Xet hash:
- 3961feb1ab51689b29a478e9a5ef8d7e38cdf56d02b5f5bfa30d2e838b1657e0
- Size of remote file:
- 16.4 MB
- SHA256:
- 0230d64c2e2e7942300a10087ef3c387982894b36e5c828f4e25f5bce7c54c07
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