Automatic Speech Recognition
MLX
meralion3
rotorquant
kv-cache-quantization
meralion
speech-to-text
multimodal
audio
quantized
4bit
apple-silicon
custom_code
Instructions to use majentik/MERaLiON-3-10B-RotorQuant-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use majentik/MERaLiON-3-10B-RotorQuant-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MERaLiON-3-10B-RotorQuant-MLX-4bit majentik/MERaLiON-3-10B-RotorQuant-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
| { | |
| "_attn_implementation_autoset": true, | |
| "_name_or_path": "/home/models/gemma2_9b-sg-inst", | |
| "architectures": [ | |
| "Gemma2ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "attn_logit_softcapping": 50.0, | |
| "cache_implementation": "hybrid", | |
| "eos_token_id": 107, | |
| "final_logit_softcapping": 30.0, | |
| "head_dim": 256, | |
| "hidden_act": "gelu_pytorch_tanh", | |
| "hidden_activation": "gelu_pytorch_tanh", | |
| "hidden_size": 3584, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 8192, | |
| "model_type": "gemma2", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 42, | |
| "num_key_value_heads": 8, | |
| "query_pre_attn_scalar": 256, | |
| "rms_norm_eps": 1e-06, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 4096, | |
| "sliding_window_size": 4096, | |
| "torch_dtype": "bfloat16", | |
| "use_cache": true, | |
| "vocab_size": 256000, | |
| "quantization": { | |
| "group_size": 64, | |
| "bits": 4, | |
| "mode": "affine" | |
| }, | |
| "quantization_config": { | |
| "group_size": 64, | |
| "bits": 4, | |
| "mode": "affine" | |
| } | |
| } |