metadata
license: apache-2.0
language:
- en
- zh
- th
- id
- vi
pipeline_tag: audio-text-to-text
tags:
- multimodal
- audio-language-model
- audio
base_model:
- mispeech/dasheng-0.6B
- Qwen/Qwen2.5-Omni-7B
base_model_relation: finetune
MiDashengLM-7B-0804 (FP8)
The FP8 weights for mispeech/midashenglm-7b-0804-fp32.
Optimized for Hopper-class (H100 and newer) GPUs, leveraging hardware support for enhanced performance and memory savings. While older GPUs may see limited performance gains, FP8 can still be used to conserve VRAM, and storage.
Usage
Load Model
from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
model_id = "mispeech/midashenglm-7b-0804-fp8"
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_id)
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
Construct Prompt
user_prompt = "Caption the audio." # You may try any other prompt
messages = [
{
"role": "user",
"content": [
{"type": "text", "text": user_prompt},
{
"type": "audio",
"path": "/path/to/example.wav",
# or "url": "https://example.com/example.wav"
# or "audio": np.random.randn(16000)
},
],
},
]
Generate Output
import torch
with torch.no_grad():
model_inputs = processor.apply_chat_template(
messages,
tokenize=True,
add_generation_prompt=True,
add_special_tokens=True,
return_dict=True,
).to(device=model.device, dtype=model.dtype)
generation = model.generate(**model_inputs)
output = tokenizer.batch_decode(generation, skip_special_tokens=True) # ["An engine is idling."]
Citation
MiDashengLM is under the Apache License 2.0, and we encourage its use in both research and business applications.
If you find MiDashengLM useful in your research, please consider citing our work:
@techreport{midashenglm7b,
title = {MiDashengLM: Efficient Audio Understanding with General Audio Captions},
author = {{Horizon Team, MiLM Plus}},
institution= {Xiaomi Inc.},
year = {2025},
note = {Contributors: Heinrich Dinkel et al. (listed alphabetically in Appendix B)},
url = {https://arxiv.org/abs/2508.03983},
eprint = {2508.03983},
}