Audio-Text-to-Text
Transformers
Safetensors
midashenglm_spatial
text-generation
spatial-audio-understanding
multimodal
audio-language-model
audio
dasheng
custom_code
Instructions to use mispeech/midashenglm-spatial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/midashenglm-spatial with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mispeech/midashenglm-spatial", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from mispeech/midashenglm-spatial: direct link, hf CLI and curl.
- Browser
- Download file 371 Bytes
-
https://huggingface.co/mispeech/midashenglm-spatial/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://mispeech/midashenglm-spatial/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/mispeech/midashenglm-spatial/resolve/main/preprocessor_config.json
371 Bytes
| { | |
| "auto_map": { | |
| "AutoProcessor": "processing_midashenglm_spatial.MiDashengLMSpatialProcessor" | |
| }, | |
| "do_normalize": false, | |
| "feature_extractor_type": "Wav2Vec2FeatureExtractor", | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "MiDashengLMSpatialProcessor", | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |