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
Download tokenizer.json from IFM/Jais-ASR-FP8: direct link, hf CLI and curl.
- Browser
- Download file 20.6 MB
-
https://huggingface.co/IFM/Jais-ASR-FP8/resolve/main/tokenizer.json
- Command line
-
hf download hf://IFM/Jais-ASR-FP8/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/IFM/Jais-ASR-FP8/resolve/main/tokenizer.json
20.6 MB
- Xet hash:
- 1400d7d42a9655c7fe11b8275f7c870c3f771f5e0a5d095256ce7359f9e16a59
- Size of remote file:
- 20.6 MB
- SHA256:
- 7e0f10516f96686b52ae4831cd83d302fe4f9224342f937c8292d3db09903634
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