Automatic Speech Recognition
Transformers
ONNX
Safetensors
ExecuTorch
English
asr4all
feature-extraction
speech
ctc
streaming
on-device
edge
custom_code
Eval Results (legacy)
Eval Results
Instructions to use futo-org/asr4all-s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use futo-org/asr4all-s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="futo-org/asr4all-s", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("futo-org/asr4all-s", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
28 days ago
-
asr4all_executorch.py: hold back ExecuTorch's own open_text deprecation warning
Verified signature745a98f -
asr4all_executorch.py: hold only the selected tier's methods (medium fp32 1.24 GB -> 0.62 GB)
Verified signatureb913645 -
asr4all_executorch.py: --tier takes a name or an index
Verified signature39c37d7 -
ONNX: one graph per component over one shared weights file; hardened scripts and modeling file
Verified signaturee0efc2e -
PCEC keep input: refreshed reference scripts (feed 0 by default), self-contained modeling file, merges in ONNX metadata
Verified signature729d7ca
-
Update release: trimmed VAD section in the model card, schema_version added to onnx/metadata.json (all metadata now v8)
Verified signature88bb29d
-
card: reduce semicolons/em-dashes, rename to Streaming tiers, fix right_ctx range wording + validation
Verified signaturec26b6ea -
reference scripts: natural-language comments, drop card-covered detail (onnx + executorch)
Verified signature567d5fc -
fir25 release: card overhaul + session(commit_chunk, right_ctx) tier-aligned API
Verified signaturee53aa54