correct vocab

README.md

@@ -1,6 +1,400 @@
 ---
 tags:
 - mms
+language:
+- ab
+- af
+- ak
+- am
+- ar
+- as
+- av
+- ay
+- az
+- ba
+- bm
+- be
+- bn
+- bi
+- bo
+- sh
+- br
+- bg
+- ca
+- cs
+- ce
+- cv
+- ku
+- cy
+- da
+- de
+- dv
+- dz
+- el
+- en
+- eo
+- et
+- eu
+- ee
+- fo
+- fa
+- fj
+- fi
+- fr
+- fy
+- ff
+- ga
+- gl
+- gn
+- gu
+- zh
+- ht
+- ha
+- he
+- hi
+- sh
+- hu
+- hy
+- ig
+- ia
+- ms
+- is
+- it
+- jv
+- ja
+- kn
+- ka
+- kk
+- kr
+- km
+- ki
+- rw
+- ky
+- ko
+- kv
+- lo
+- la
+- lv
+- ln
+- lt
+- lb
+- lg
+- mh
+- ml
+- mr
+- ms
+- mk
+- mg
+- mt
+- mn
+- mi
+- my
+- zh
+- nl
+- 'no'
+- 'no'
+- ne
+- ny
+- oc
+- om
+- or
+- os
+- pa
+- pl
+- pt
+- ms
+- ps
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- qu
+- ro
+- rn
+- ru
+- sg
+- sk
+- sl
+- sm
+- sn
+- sd
+- so
+- es
+- sq
+- su
+- sv
+- sw
+- ta
+- tt
+- te
+- tg
+- tl
+- th
+- ti
+- ts
+- tr
+- uk
+- ms
+- vi
+- wo
+- xh
+- ms
+- yo
+- ms
+- zu
+- za
+license: cc-by-sa-4.0
+datasets:
+- google/fleurs
+metrics:
+- wer
 ---
 
-[WIP]: See: https://github.com/huggingface/transformers/pull/23813
+# Massively Multilingual Speech (MMS) - Finetuned ASR - ALL
+
+This checkpoint is a model fine-tuned for multi-lingual ASR and part of Facebook's [Massive Multilingual Speech project](https://research.facebook.com/publications/scaling-speech-technology-to-1000-languages/).
+This checkpoint is based on the [Wav2Vec2 architecture](https://huggingface.co/docs/transformers/model_doc/wav2vec2) and makes use of adapter models to transcribe 100+ languages.
+The checkpoint consists of **1 billion parameters** and has been fine-tuned from [facebook/mms-1b](https://huggingface.co/facebook/mms-1b) on 102 languages of [Fleurs](https://huggingface.co/datasets/google/fleurs).
+
+## Table Of Content
+
+- [Example](#example)
+- [Supported Languages](#supported-languages)
+- [Model details](#model-details)
+- [Additional links](#additional-links)
+
+## Example
+
+This MMS checkpoint can be used with [Transformers](https://github.com/huggingface/transformers) to transcribe audio of 1107 different 
+languages. Let's look at a simple example.
+
+First, we install transformers and some other libraries
+```
+pip install torch accelerate torchaudio datasets
+pip install --upgrade transformers
+````
+
+**Note**: In order to use MMS you need to have at least `transformers >= 4.30` installed. If the `4.30` version
+is not yet available [on PyPI](https://pypi.org/project/transformers/) make sure to install `transformers` from 
+source:
+```
+pip install git+https://github.com/huggingface/transformers.git
+```
+
+Next, we load a couple of audio samples via `datasets`. Make sure that the audio data is sampled to 16000 kHz.
+
+```py
+from datasets import load_dataset, Audio
+
+# English
+stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "en", split="test", streaming=True)
+stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
+en_sample = next(iter(stream_data))["audio"]["array"]
+
+# French
+stream_data = load_dataset("mozilla-foundation/common_voice_13_0", "fr", split="test", streaming=True)
+stream_data = stream_data.cast_column("audio", Audio(sampling_rate=16000))
+fr_sample = next(iter(stream_data))["audio"]["array"]
+```
+
+Next, we load the model and processor
+
+```py
+from transformers import Wav2Vec2ForCTC, AutoProcessor
+import torch
+
+model_id = "facebook/mms-1b-fl102"
+
+processor = AutoProcessor.from_pretrained(model_id)
+model = Wav2Vec2ForCTC.from_pretrained(model_id)
+```
+
+Now we process the audio data, pass the processed audio data to the model and transcribe the model output, just like we usually do for Wav2Vec2 models such as [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h)
+
+```py
+inputs = processor(en_sample, sampling_rate=16_000, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model(**inputs).logits
+
+ids = torch.argmax(outputs, dim=-1)[0]
+transcription = processor.decode(ids)
+# 'joe keton disapproved of films and buster also had reservations about the media'
+```
+
+We can now keep the same model in memory and simply switch out the language adapters by calling the convenient [`load_adapter()`]() function for the model and [`set_target_lang()`]() for the tokenizer. We pass the target language as an input - "fra" for French.
+
+```py
+processor.tokenizer.set_target_lang("fra")
+model.load_adapter("fra")
+
+inputs = processor(fr_sample, sampling_rate=16_000, return_tensors="pt")
+
+with torch.no_grad():
+    outputs = model(**inputs).logits
+
+ids = torch.argmax(outputs, dim=-1)[0]
+transcription = processor.decode(ids)
+# "ce dernier est volé tout au long de l'histoire romaine"
+```
+
+In the same way the language can be switched out for all other supported languages. Please have a look at:
+```py
+processor.tokenizer.vocab.keys()
+```
+
+For more details, please have a look at [the official docs](https://huggingface.co/docs/transformers/main/en/model_doc/mms).
+
+## Supported Languages
+
+This model supports 102 languages. Unclick the following to toogle all supported languages of this checkpoint in [ISO 639-3 code](https://en.wikipedia.org/wiki/ISO_639-3).
+You can find more details about the languages and their ISO 649-3 codes in the [MMS Language Coverage Overview](https://dl.fbaipublicfiles.com/mms/misc/language_coverage_mms.html).
+<details>
+  <summary>Click to toggle</summary>
+
+- afr
+- amh
+- ara
+- asm
+- ast
+- azj-script_latin
+- bel
+- ben
+- bos
+- bul
+- cat
+- ceb
+- ces
+- ckb
+- cmn-script_simplified
+- cym
+- dan
+- deu
+- ell
+- eng
+- est
+- fas
+- fin
+- fra
+- ful
+- gle
+- glg
+- guj
+- hau
+- heb
+- hin
+- hrv
+- hun
+- hye
+- ibo
+- ind
+- isl
+- ita
+- jav
+- jpn
+- kam
+- kan
+- kat
+- kaz
+- kea
+- khm
+- kir
+- kor
+- lao
+- lav
+- lin
+- lit
+- ltz
+- lug
+- luo
+- mal
+- mar
+- mkd
+- mlt
+- mon
+- mri
+- mya
+- nld
+- nob
+- npi
+- nso
+- nya
+- oci
+- orm
+- ory
+- pan
+- pol
+- por
+- pus
+- ron
+- rus
+- slk
+- slv
+- sna
+- snd
+- som
+- spa
+- srp-script_latin
+- swe
+- swh
+- tam
+- tel
+- tgk
+- tgl
+- tha
+- tur
+- ukr
+- umb
+- urd-script_arabic
+- uzb-script_latin
+- vie
+- wol
+- xho
+- yor
+- yue-script_traditional
+- zlm
+- zul
+
+</details>
+
+## Model details
+
+- **Developed by:** Vineel Pratap et al.
+- **Model type:** Multi-Lingual Automatic Speech Recognition model
+- **Language(s):** 1107+ languages, see [supported languages](#supported-languages)
+- **License:** CC-BY-NC 4.0 license
+- **Num parameters**: 1 billion
+- **Cite as:**
+
+      @article{pratap2023mms,
+        title={Scaling Speech Technology to 1,000+ Languages},
+        author={Vineel Pratap and Andros Tjandra and Bowen Shi and Paden Tomasello and Arun Babu and Sayani Kundu and Ali Elkahky and Zhaoheng Ni and Apoorv Vyas and Maryam Fazel-Zarandi and Alexei Baevski and Yossi Adi and Xiaohui Zhang and Wei-Ning Hsu and Alexis Conneau and Michael Auli},
+      journal={arXiv},
+      year={2023}
+      }
+
+## Additional Links
+
+- [Blog post]( )
+- [Transformers documentation](https://huggingface.co/docs/transformers/main/en/model_doc/mms).
+- [Paper](https://arxiv.org/abs/2305.13516)
+- [GitHub Repository](https://github.com/facebookresearch/fairseq/tree/main/examples/mms#asr)
+- [Other **MMS** checkpoints](https://huggingface.co/models?other=mms)
+- [Official Space](https://huggingface.co/spaces/facebook/MMS)