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-41400/rng_state.pth from codingninja/w2v-pa-v2: direct link, hf CLI and curl.
- Browser
- Download file 14.2 kB
-
https://huggingface.co/codingninja/w2v-pa-v2/resolve/main/checkpoint-41400/rng_state.pth
- Command line
-
hf download hf://codingninja/w2v-pa-v2/checkpoint-41400/rng_state.pth
-
curl -L -o rng_state.pth https://huggingface.co/codingninja/w2v-pa-v2/resolve/main/checkpoint-41400/rng_state.pth
14.2 kB
- Xet hash:
- 36ddef88e3bee5eea751244a00f0d2ff38c89f3b32ba00d61b7f8065d52596d0
- Size of remote file:
- 14.2 kB
- SHA256:
- fee0fcaf3c71f5c60aa31135f5e7946ac5bc78ae5349178488b3b1cdca1ae554
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