Text Generation
MLX
Safetensors
English
Chinese
mimo_v2
omlx
oq
oq4
quantized
4-bit precision
text-only
Mixture of Experts
long-context
conversational
custom_code
Instructions to use Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Blightbow/MiMo-V2.5-Text-Only-oQ4-MLX" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
| { | |
| "architectures": [ | |
| "MiMoV2ForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_mimo_v2.MiMoV2Config", | |
| "AutoModel": "modeling_mimo_v2.MiMoV2Model", | |
| "AutoModelForCausalLM": "modeling_mimo_v2.MiMoV2ForCausalLM" | |
| }, | |
| "attention_bias": false, | |
| "attention_chunk_size": 128, | |
| "attention_dropout": 0.0, | |
| "attention_value_scale": 0.707, | |
| "attention_projection_layout": "fused_qkv", | |
| "add_full_attention_sink_bias": false, | |
| "add_swa_attention_sink_bias": true, | |
| "swa_num_key_value_heads": 8, | |
| "swa_num_attention_heads": 64, | |
| "swa_head_dim": 192, | |
| "swa_v_head_dim": 128, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 151645, | |
| "head_dim": 192, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "hybrid_block_size": null, | |
| "hybrid_layer_pattern": [ | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 0 | |
| ], | |
| "initializer_range": 0.02, | |
| "intermediate_size": 16384, | |
| "layernorm_epsilon": 1e-05, | |
| "max_position_embeddings": 1048576, | |
| "model_type": "mimo_v2", | |
| "moe_intermediate_size": 2048, | |
| "moe_layer_freq": [ | |
| 0, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1, | |
| 1 | |
| ], | |
| "n_group": 1, | |
| "n_routed_experts": 256, | |
| "n_shared_experts": null, | |
| "norm_topk_prob": true, | |
| "num_attention_heads": 64, | |
| "num_experts_per_tok": 8, | |
| "num_hidden_layers": 48, | |
| "num_key_value_heads": 4, | |
| "pad_token_id": 151643, | |
| "partial_rotary_factor": 0.334, | |
| "processor_config": { | |
| "audio_avg_pooler": 2, | |
| "audio_channels": 20, | |
| "audio_end_token_id": 151674, | |
| "audio_fmax": null, | |
| "audio_fmin": 0, | |
| "audio_group_size": 4, | |
| "audio_hop_length": 240, | |
| "audio_input_id_per_second": 25.0, | |
| "audio_kernel_size": 3, | |
| "audio_n_mels": 128, | |
| "audio_nfft": 960, | |
| "audio_sampling_rate": 24000, | |
| "audio_segment_size": 6000, | |
| "audio_start_token_id": 151673, | |
| "audio_stride_size": 2, | |
| "audio_token_id": 151669, | |
| "audio_window_size": 960, | |
| "audio_zeroemb_idx": [ | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024 | |
| ], | |
| "fps": 1.0, | |
| "image_max_pixels": 8388608, | |
| "image_min_pixels": 8192, | |
| "image_token_id": 151655, | |
| "max_frames": 3600, | |
| "merge_size": 2, | |
| "min_frames": null, | |
| "num_frames": null, | |
| "pad_token_id": 151643, | |
| "patch_size": 16, | |
| "rope_type": "rope", | |
| "temporal_compression_ratio": 1, | |
| "temporal_patch_size": 2, | |
| "use_per_grid_t_timestamps": false, | |
| "use_video_timestamps": true, | |
| "video_audio_interleave_length": 0.0, | |
| "video_end_token_id": 151671, | |
| "video_max_pixels": 8388608, | |
| "video_min_pixels": 8192, | |
| "video_process_num_threads": 16, | |
| "video_start_token_id": 151670, | |
| "video_token_id": 151656, | |
| "video_tokens_per_second": 2, | |
| "video_total_max_pixels": 268435456, | |
| "vision_end_token_id": 151653, | |
| "vision_start_token_id": 151652 | |
| }, | |
| "quantization_config": { | |
| "group_size": 64, | |
| "bits": 4, | |
| "mode": "affine", | |
| "lm_head": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.embed_tokens": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.down_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.gate_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.up_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| } | |
| }, | |
| "rope_scaling": { | |
| "rope_type": "default", | |
| "type": "default" | |
| }, | |
| "rope_theta": 10000000, | |
| "routed_scaling_factor": null, | |
| "scoring_func": "sigmoid", | |
| "sliding_window": 128, | |
| "sliding_window_size": 128, | |
| "swa_rope_theta": 10000, | |
| "tie_word_embeddings": false, | |
| "topk_group": 1, | |
| "topk_method": "noaux_tc", | |
| "transformers_version": "4.57.1", | |
| "use_cache": true, | |
| "v_head_dim": 128, | |
| "vision_model_type": "mimovl", | |
| "vocab_size": 152576, | |
| "quantization": { | |
| "group_size": 64, | |
| "bits": 4, | |
| "mode": "affine", | |
| "lm_head": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.embed_tokens": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.o_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.down_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.gate_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.mlp.up_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.0.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.1.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.2.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.3.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.4.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.5.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.6.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.7.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.8.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.9.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.10.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.11.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.12.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.13.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.14.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.15.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.16.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.17.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.18.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.19.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.20.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.21.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.22.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.23.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.24.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.25.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.26.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.27.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.28.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.29.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.30.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.31.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.32.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.33.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.34.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.35.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.36.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.37.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.38.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.39.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.40.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.41.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.42.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.43.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.44.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.45.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.46.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.q_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.k_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| }, | |
| "model.layers.47.self_attn.v_proj": { | |
| "bits": 8, | |
| "group_size": 64, | |
| "mode": "affine" | |
| } | |
| } | |
| } |