Instructions to use BigSalmon/Concise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BigSalmon/Concise with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("BigSalmon/Concise") model = AutoModelForSeq2SeqLM.from_pretrained("BigSalmon/Concise", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BigSalmon/Concise: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/BigSalmon/Concise/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://BigSalmon/Concise@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BigSalmon/Concise/resolve/refs%2Fpr%2F1/pytorch_model.bin
892 MB
- Xet hash:
- 338a7ca5bacfd6eb05707a48b4c49a1ad62a935a61dcc441b54b8629b952c04e
- Size of remote file:
- 892 MB
- SHA256:
- ca958a050c74378e07cb022df210458b5310a078be0ad8e9e38bb591249be8aa
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