Hugging Face's logo

davidmeikle
/
whisper-medium-eole

Automatic Speech Recognition
Safetensors
audio
eole
whisper
Model card Files
xet
Community
whisper-medium-eole
File size: 2,140 Bytes
f441ae0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
 
---
language:
- en
- zh
- de
- es
- ru
- ko
- fr
- ja
- pt
- tr
- pl
- ca
- nl
- ar
- sv
- it
- id
- hi
- fi
- vi
- he
- uk
- el
- ms
- cs
- ro
- da
- hu
- ta
- "no"
- th
- ur
- hr
- bg
- lt
- la
- mi
- ml
- cy
- sk
- te
- fa
- lv
- bn
- sr
- az
- sl
- kn
- et
- mk
- br
- eu
- is
- hy
- ne
- mn
- bs
- kk
- sq
- sw
- gl
- mr
- pa
- si
- km
- sn
- yo
- so
- af
- oc
- ka
- be
- tg
- sd
- gu
- am
- yi
- lo
- uz
- fo
- ht
- ps
- tk
- nn
- mt
- sa
- lb
- my
- bo
- tl
- mg
- as
- tt
- haw
- ln
- ha
- ba
- jw
- su
tags:
- audio
- automatic-speech-recognition
- eole
- whisper
license: apache-2.0
base_model: openai/whisper-medium
pipeline_tag: automatic-speech-recognition
---

# Whisper Medium (eole)

This is [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) converted to [eole](https://github.com/eole-nlp/eole) format using `eole convert --model_dir openai/whisper-medium`.

No weights were modified — this is a format conversion only.

## Model details

| | |
|---|---|
| **Original model** | [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) |
| **Parameters** | 769M |
| **Encoder layers** | 24 |
| **Decoder layers** | 24 |
| **Hidden size** | 1024 |
| **Attention heads** | 16 |
| **Mel bins** | 80 |
| **Vocab size** | 51,865 |
| **License** | Apache 2.0 |

## Usage

```bash
pip install eole[wer]
```

### Transcribe

```bash
eole predict \
  -config eval_config.yaml \
  -model_path whisper-medium-eole \
  -src audio_files.txt \
  -output transcriptions.txt \
  -language en \
  -task transcribe \
  -gpu_ranks 0
```

## Evaluation

All evaluations use beam size 5.

| Benchmark | WER |
|---|---|
| LibriSpeech test-clean | 2.92% |

## Conversion

```bash
eole convert --model_dir openai/whisper-medium --output whisper-medium-eole
```

## Citation

```bibtex
@misc{radford2023robust,
      title={Robust Speech Recognition via Large-Scale Weak Supervision},
      author={Alec Radford and Jong Wook Kim and Tao Xu and Greg Brockman and Christine McLeavey and Ilya Sutskever},
      year={2023},
      eprint={2212.04356},
      archivePrefix={arXiv},
      primaryClass={eess.AS}
}
```