Instructions to use jla25/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jla25/results with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jla25/results") model = AutoModelForSeq2SeqLM.from_pretrained("jla25/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jla25/results: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/jla25/results/resolve/main/training_args.bin
- Command line
-
hf download hf://jla25/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jla25/results/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 9b8c571433383f96ee95d08277c09eeea69be7d3f749ff5eeb2b567da9b5f18f
- Size of remote file:
- 5.3 kB
- SHA256:
- 1536002bf25986431e671d77b62cc7b0088f40df2a457cd584ad85bba45c394a
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