Instructions to use madoss/w2v-bert-2.0-mongolian-colab-CV16.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madoss/w2v-bert-2.0-mongolian-colab-CV16.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="madoss/w2v-bert-2.0-mongolian-colab-CV16.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("madoss/w2v-bert-2.0-mongolian-colab-CV16.0") model = AutoModelForCTC.from_pretrained("madoss/w2v-bert-2.0-mongolian-colab-CV16.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from madoss/w2v-bert-2.0-mongolian-colab-CV16.0: direct link, hf CLI and curl.
- Browser
- Download file 5.27 kB
-
https://huggingface.co/madoss/w2v-bert-2.0-mongolian-colab-CV16.0/resolve/main/training_args.bin
- Command line
-
hf download hf://madoss/w2v-bert-2.0-mongolian-colab-CV16.0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/madoss/w2v-bert-2.0-mongolian-colab-CV16.0/resolve/main/training_args.bin
5.27 kB
- Xet hash:
- f1245b149d674000be6d9a1d96753f058f50414fb07df8d2037be7dc02a62a99
- Size of remote file:
- 5.27 kB
- SHA256:
- 94cb5c961bd77a867f8c45fd586097290797df08249e373ac51f1a081410412b
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