Instructions to use BigSalmon/ConciseAndFormal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/ConciseAndFormal with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/ConciseAndFormal") model = AutoModelForSeq2SeqLM.from_pretrained("BigSalmon/ConciseAndFormal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BigSalmon/ConciseAndFormal: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/BigSalmon/ConciseAndFormal/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://BigSalmon/ConciseAndFormal@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BigSalmon/ConciseAndFormal/resolve/refs%2Fpr%2F1/pytorch_model.bin
892 MB
- Xet hash:
- f7205ebf38229edcea5d83cc87bdad76db6e47900037c2d366ecd9642da42175
- Size of remote file:
- 892 MB
- SHA256:
- 08597260c12646ad3d9cbb19399769c90036aeb2a26f8c3b0e7d7f3922cb262a
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