Instructions to use codingninja/w2v-pa-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codingninja/w2v-pa-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="codingninja/w2v-pa-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("codingninja/w2v-pa-v2") model = AutoModelForCTC.from_pretrained("codingninja/w2v-pa-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-84600/scheduler.pt from codingninja/w2v-pa-v2: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/codingninja/w2v-pa-v2/resolve/main/checkpoint-84600/scheduler.pt
- Command line
-
hf download hf://codingninja/w2v-pa-v2/checkpoint-84600/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/codingninja/w2v-pa-v2/resolve/main/checkpoint-84600/scheduler.pt
1.06 kB
- Xet hash:
- ba8b404f44e525c1e46c4e5c11d5a72909d5f78768296e92cffea83c54e44f44
- Size of remote file:
- 1.06 kB
- SHA256:
- 739c30d3202de1471085c40f21f2437177e314c2f3f2bc2e392295f6ba2dd2a4
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