Instructions to use ativilambit/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ativilambit/results with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ativilambit/results") model = AutoModelForSeq2SeqLM.from_pretrained("ativilambit/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ativilambit/results: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/ativilambit/results/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ativilambit/results/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ativilambit/results/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- d2fb01b1e27982fda529b452366a52b6899a8746d208a2b1aed4b40f92bd6c48
- Size of remote file:
- 990 MB
- SHA256:
- 60568ddd5bf9e9e17232e8c1921f2fae0d8027d868cfcc60b52de61e7e181fad
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