Instructions to use longcld/longdemo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use longcld/longdemo with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("longcld/longdemo") model = AutoModelForSeq2SeqLM.from_pretrained("longcld/longdemo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from longcld/longdemo: direct link, hf CLI and curl.
- Browser
- Download file 3.17 GB
-
https://huggingface.co/longcld/longdemo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://longcld/longdemo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/longcld/longdemo/resolve/main/pytorch_model.bin
3.17 GB
- Xet hash:
- 0d9b4e2dd4bcd4fd62b68b8adc9b6b3749e6f16d1c0bc8581a13709e361d9d63
- Size of remote file:
- 3.17 GB
- SHA256:
- 9f0e8c84d3e37db5751dba6730722185d4d803b470041864abf112078cd09f96
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.