Instructions to use Seungyoun/Kimi-Audio-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Seungyoun/Kimi-Audio-7B-Instruct with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Seungyoun/Kimi-Audio-7B-Instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Seungyoun/Kimi-Audio-7B-Instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("Seungyoun/Kimi-Audio-7B-Instruct", trust_remote_code=True, device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Seungyoun/Kimi-Audio-7B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Seungyoun/Kimi-Audio-7B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Seungyoun/Kimi-Audio-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Seungyoun/Kimi-Audio-7B-Instruct

SGLang

How to use Seungyoun/Kimi-Audio-7B-Instruct 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 "Seungyoun/Kimi-Audio-7B-Instruct" \
    --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": "Seungyoun/Kimi-Audio-7B-Instruct",
		"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 "Seungyoun/Kimi-Audio-7B-Instruct" \
        --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": "Seungyoun/Kimi-Audio-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Seungyoun/Kimi-Audio-7B-Instruct with Docker Model Runner:
```
docker model run hf.co/Seungyoun/Kimi-Audio-7B-Instruct
```

Seungyoun commited on Apr 29, 2025

Commit

819a415

verified ·

1 Parent(s): 2413ef5

Update preprocessor_config.json

Browse files

Files changed (1) hide show

preprocessor_config.json +14 -13

preprocessor_config.json CHANGED Viewed

@@ -1,15 +1,16 @@
 {
-    "feature_extractor_type": "WhisperFeatureExtractor",
-    "sampling_rate": 16000,
-    "return_attention_mask": true,
-    "padding": "max_length",
-    "chunk_length": 300,
-    "n_samples": 4800000,
-    "nb_max_frames": 30000,
-    "n_fft": 400,
-    "hop_length": 160,
-    "dither": 0.0,
-    "padding_side": "left",
-    "processor_class": "KimiAudioProcessor"
-  }

 {
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "sampling_rate": 16000,
+  "return_attention_mask": true,
+  "padding": "max_length",
+  "chunk_length": 300,
+  "n_samples": 4800000,
+  "nb_max_frames": 30000,
+  "n_fft": 400,
+  "hop_length": 160,
+  "dither": 0.0,
+  "padding_side": "left",
+  "tokenizer_class": "Qwen2TokenizerFast",
+  "processor_class": "KimiAudioProcessor"
+}