Instructions to use xdwang/tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xdwang/tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="xdwang/tmp")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("xdwang/tmp") model = AutoModelForCTC.from_pretrained("xdwang/tmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from xdwang/tmp: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/xdwang/tmp/resolve/main/training_args.bin
- Command line
-
hf download hf://xdwang/tmp/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/xdwang/tmp/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- 5688a9f701c0a03371d088c6bb4c1f01ce85d868f85a4b4bfd94eea31e599c61
- Size of remote file:
- 2.99 kB
- SHA256:
- bd20da039bb499c800f26ae982c1e5b0ca73b588f2cd59f7d574e06b071a9553
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