Instructions to use bezzam/Fun-ASR-Nano-2512-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/Fun-ASR-Nano-2512-hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bezzam/Fun-ASR-Nano-2512-hf") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("bezzam/Fun-ASR-Nano-2512-hf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bezzam/Fun-ASR-Nano-2512-hf with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bezzam/Fun-ASR-Nano-2512-hf" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bezzam/Fun-ASR-Nano-2512-hf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bezzam/Fun-ASR-Nano-2512-hf
- SGLang
How to use bezzam/Fun-ASR-Nano-2512-hf with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "bezzam/Fun-ASR-Nano-2512-hf" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bezzam/Fun-ASR-Nano-2512-hf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "bezzam/Fun-ASR-Nano-2512-hf" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bezzam/Fun-ASR-Nano-2512-hf", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use bezzam/Fun-ASR-Nano-2512-hf with Docker Model Runner:
docker model run hf.co/bezzam/Fun-ASR-Nano-2512-hf
| { | |
| "audio_token": "<|object_ref_start|>", | |
| "default_transcription_prompt": "Transcribe the audio:", | |
| "feature_extractor": { | |
| "feature_extractor_type": "FunAsrNanoFeatureExtractor", | |
| "feature_size": 80, | |
| "frame_length": 25, | |
| "frame_shift": 10, | |
| "lfr_m": 7, | |
| "lfr_n": 6, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "preemphasis": 0.97, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| }, | |
| "processor_class": "FunAsrNanoProcessor" | |
| } | |