Instructions to use nadsoft/hamsa-v0.1-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nadsoft/hamsa-v0.1-beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nadsoft/hamsa-v0.1-beta")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nadsoft/hamsa-v0.1-beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("nadsoft/hamsa-v0.1-beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:485b2855cd8eb158a85095421c29c1375fa65c4a63b10573310e05e03c89ea05
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size 3055544360
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