Instructions to use ShynBui/s3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShynBui/s3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ShynBui/s3")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ShynBui/s3") model = AutoModelForQuestionAnswering.from_pretrained("ShynBui/s3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ShynBui/s3: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/ShynBui/s3/resolve/main/training_args.bin
- Command line
-
hf download hf://ShynBui/s3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ShynBui/s3/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- ec0d6f24ffc02ec4851ba994830ceea8f4d82e1935ee139e589a3bccd13588b2
- Size of remote file:
- 3.96 kB
- SHA256:
- 01bf8d2e0c9487867a8b907e50645eb565b918ef108de5d6e4d0fee2e9bde617
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.