Automatic Speech Recognition
Transformers
Safetensors
jais_asr
text-generation
jais
ifm
arabic
arabic-dialects
speech-to-text
code-switching
diacritization
language-identification
open-weights
custom_code
Instructions to use IFM/Jais-ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IFM/Jais-ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="IFM/Jais-ASR", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("IFM/Jais-ASR", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from IFM/Jais-ASR: direct link, hf CLI and curl.
- Browser
- Download file 211 Bytes
-
https://huggingface.co/IFM/Jais-ASR/resolve/main/processor_config.json
- Command line
-
hf download hf://IFM/Jais-ASR/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/IFM/Jais-ASR/resolve/main/processor_config.json
211 Bytes
| { | |
| "audio_token": "<|ifm|audio|>", | |
| "auto_map": { | |
| "AutoProcessor": "processing_jais_asr.JaisASRProcessor" | |
| }, | |
| "boa_token": "<audio>", | |
| "eoa_token": "</audio>", | |
| "processor_class": "JaisASRProcessor" | |
| } |