Instructions to use Haopeng/MDD-LLM-Llama3.2-1B-L2-ARCTIC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- speechbrain
How to use Haopeng/MDD-LLM-Llama3.2-1B-L2-ARCTIC with speechbrain:
# interface not specified in config.json
- Notebooks
- Google Colab
- Kaggle
MDD-LLM with Llama 3.2 1B for L2-ARCTIC
This repository is a standalone IF-MDD inference bundle. It includes the
complete model.ckpt inference state, the verified 44-label encoder,
bundle-local Llama tokenizer and WavLM configuration, and all runtime modules needed by the wrapper, so loading
does not contact Hugging Face.
Download
python -m pip install -U huggingface_hub
hf download Haopeng/MDD-LLM-Llama3.2-1B-L2-ARCTIC --local-dir MDD-LLM-Llama3.2-1B-L2-ARCTIC
cd MDD-LLM-Llama3.2-1B-L2-ARCTIC
Single WAV
pip install -r requirements.txt
python custom_interface.py \
--hparams-file hyperparams.yaml \
--audio /path/to/audio.wav \
--override 'prompt_system_text=You are a pronunciation evaluator.' \
--override 'prompt_user_text=Return only the perceived phoneme sequence.'
Repository Eval
With the main branch:
python train.py hparams/MDD_LLM_Llama3_2_1B.yaml \
--mode eval \
--inference_ckpt /path/to/MDD-LLM-Llama3.2-1B-L2-ARCTIC
Set HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1 to enforce offline loading.
manifest.json records the required recoverables, architecture signature,
defaults, and label-encoder SHA256.
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Model tree for Haopeng/MDD-LLM-Llama3.2-1B-L2-ARCTIC
Base model
meta-llama/Llama-3.2-1B-Instruct