Automatic Speech Recognition
MLX
ONNX
GGUF
Rust
English
Chinese
audio8
streaming-asr
quantized
experimental
Instructions to use Reza2kn/Audio8-ASR-Infinite-Compressed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Reza2kn/Audio8-ASR-Infinite-Compressed with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download Reza2kn/Audio8-ASR-Infinite-Compressed --local-dir Audio8-ASR-Infinite-Compressed
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 2,667 Bytes
c49eca9 | 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 | """Bind every visible caption delta to its producing token before scoring time."""
from probe_native_stream import token_table, token_oracle
from validate_caption_run import validate as validate_accounting, require
def validate(rows, observations, case, tokenizer, *, frozen_segments=None, expected_ids=None):
table = token_table(tokenizer)
active = None
prior_visible = False
global_count = 0
for row in rows:
kind = row['kind']
if kind == 'caption_segment_start':
require(active is None, 'overlapping caption segments')
active = dict(id=row['segment'], base=global_count, ids=[], deltas=[])
elif kind == 'caption_text_delta':
require(active is not None and row['segment'] == active['id'], 'caption delta segment identity')
require(type(row.get('index')) is int and row['index'] == global_count,
'caption delta not emitted at its declared token clock')
require(type(row.get('text')) is str and bool(row['text']), 'empty/invalid caption delta')
flush = row.get('utf8_final_flush', False)
separator = row.get('segment_separator', False)
require(type(flush) is bool and type(separator) is bool and not (flush and separator),
'caption delta flags differ')
active['deltas'].append((row['index'] - active['base'], row['text'], flush, separator))
elif kind == 'caption_window':
require(active is not None and row['segment'] == active['id'], 'caption token segment identity')
require(row['index'] == global_count, 'caption token clock differs')
active['ids'].append(row['token_id'])
global_count += 1
elif kind == 'caption_segment_end':
require(active is not None and row['segment'] == active['id'], 'caption end segment identity')
oracle = token_oracle(active['ids'], table)
expected = [(index, text, flush, False) for index, text, flush in oracle['deltas']]
if expected:
if prior_visible:
expected.insert(0, (expected[0][0], '\n', False, True))
prior_visible = True
require(active['deltas'] == expected, 'caption delta index/text/flush/separator differs from token oracle')
active = None
require(active is None, 'unfinished caption delta segment')
result = validate_accounting(rows, observations, case, tokenizer,
frozen_segments=frozen_segments, expected_ids=expected_ids)
result['independent_delta_token_clock_oracle'] = True
return result
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