Instructions to use bezzam/Fun-ASR-Nano-2512-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

Fun-ASR-Nano-2512-hf

File size: 482 Bytes

9b569e3

{
  "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"
}