Automatic Speech Recognition
Transformers
Safetensors
Chinese
English
Yue Chinese
qwen2
text-generation
text-generation-inference
Instructions to use fengjay01/MiMo-V2.5-ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fengjay01/MiMo-V2.5-ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="fengjay01/MiMo-V2.5-ASR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("fengjay01/MiMo-V2.5-ASR") model = AutoModelForCausalLM.from_pretrained("fengjay01/MiMo-V2.5-ASR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from fengjay01/MiMo-V2.5-ASR: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/fengjay01/MiMo-V2.5-ASR/resolve/main/tokenizer.json
- Command line
-
hf download hf://fengjay01/MiMo-V2.5-ASR/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/fengjay01/MiMo-V2.5-ASR/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 927e3a3ccafe546f7481b347949acc9ed02e819462c48d526d4abd5d5bf9d006
- Size of remote file:
- 11.4 MB
- SHA256:
- d91a78cce6441fd6855038f6764fc5f811ae949d9b89f43ac326cddfe91c66db
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