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
fp8
compressed-tensors
llm-compressor
Instructions to use IFM/Jais-ASR-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IFM/Jais-ASR-FP8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="IFM/Jais-ASR-FP8", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("IFM/Jais-ASR-FP8", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 520 Bytes
72b5b09 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"auto_map": {
"AutoProcessor": "processing_jais_asr.JaisASRProcessor"
},
"backend": "tokenizers",
"bos_token": "<|ifm|begin_of_text|>",
"clean_up_tokenization_spaces": false,
"eos_token": "<|ifm|im_end|>",
"is_local": true,
"local_files_only": false,
"model_input_names": [
"input_ids",
"attention_mask"
],
"model_max_length": 32768,
"pad_token": "<|ifm|begin_of_text|>",
"padding_side": "left",
"processor_class": "JaisASRProcessor",
"tokenizer_class": "TokenizersBackend"
}
|