Automatic Speech Recognition
Transformers
Safetensors
English
Italian
conformer_encoder_decoder
speech
speech recognition
ASR
custom_code
Instructions to use FBK-MT/fama-medium-asr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FBK-MT/fama-medium-asr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="FBK-MT/fama-medium-asr", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("FBK-MT/fama-medium-asr", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name and link to code (#1)
Browse files- Add pipeline tag, library name and link to code (924d2fff372eb09491a2a618e871c674bdf0b10f)
Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>
README.md
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---
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license: cc-by-4.0
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language:
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- en
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- it
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datasets:
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- FBK-MT/mosel
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- facebook/covost2
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- openslr/librispeech_asr
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- facebook/voxpopuli
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metrics:
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- wer
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tags:
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- speech
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- speech recognition
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- ASR
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---
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# FAMA-medium-asr
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themself are [released under OS-compliant licenses](#license), promoting a more
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responsible creation of models in our community.
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It is available in 2 sizes, with 2 variants for ASR only:
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- [FAMA-small](https://huggingface.co/FBK-MT/fama-small) - 475 million parameters
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For more information about FAMA, please check our [blog post](https://huggingface.co/blog/FAMA/release) and the [arXiv](https://arxiv.org/abs/2505.22759) preprint.
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## Usage
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---
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datasets:
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- FBK-MT/mosel
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- facebook/covost2
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- openslr/librispeech_asr
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- facebook/voxpopuli
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language:
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- en
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- it
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license: cc-by-4.0
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metrics:
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- wer
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tags:
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- speech
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- speech recognition
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- ASR
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library_name: fairseq
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pipeline_tag: automatic-speech-recognition
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---
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# FAMA-medium-asr
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themself are [released under OS-compliant licenses](#license), promoting a more
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responsible creation of models in our community.
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It is available in 2 sizes, with 2 variants for ASR only:
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- [FAMA-small](https://huggingface.co/FBK-MT/fama-small) - 475 million parameters
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For more information about FAMA, please check our [blog post](https://huggingface.co/blog/FAMA/release) and the [arXiv](https://arxiv.org/abs/2505.22759) preprint.
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Code is available at https://github.com/hlt-mt/FBK-fairseq
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## Usage
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