Image-Text-to-Text
MLX
Safetensors
inkling_mm_model
Mixture of Experts
multimodal
inkling
thinking-machines
conversational
Instructions to use pipenetwork/Inkling-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use pipenetwork/Inkling-MLX-4bit with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("pipenetwork/Inkling-MLX-4bit") config = load_config("pipenetwork/Inkling-MLX-4bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use pipenetwork/Inkling-MLX-4bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "pipenetwork/Inkling-MLX-4bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "pipenetwork/Inkling-MLX-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use pipenetwork/Inkling-MLX-4bit 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 "pipenetwork/Inkling-MLX-4bit"
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 pipenetwork/Inkling-MLX-4bit
Run Hermes
hermes
- OpenClaw new
How to use pipenetwork/Inkling-MLX-4bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "pipenetwork/Inkling-MLX-4bit"
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 "pipenetwork/Inkling-MLX-4bit" \ --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": [ | |
| "InklingForConditionalGeneration" | |
| ], | |
| "model_type": "inkling_mm_model", | |
| "eos_token_id": 200006, | |
| "text_config": { | |
| "model_max_length": 1048576, | |
| "torch_dtype": "bfloat16", | |
| "hidden_size": 6144, | |
| "num_hidden_layers": 66, | |
| "vocab_size": 201024, | |
| "num_attention_heads": 64, | |
| "num_key_value_heads": 8, | |
| "head_dim": 128, | |
| "d_rel": 16, | |
| "rel_extent": 1024, | |
| "q_bias": false, | |
| "o_bias": false, | |
| "log_scaling_n_floor": 128000, | |
| "log_scaling_alpha": 0.1, | |
| "rms_norm_eps": 1e-06, | |
| "use_embed_norm": true, | |
| "local_layer_ids": [ | |
| 0, | |
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| ], | |
| "dense_mlp_idx": 2, | |
| "use_sconv": true, | |
| "sconv_kernel_size": 4, | |
| "unpadded_vocab_size": 200058, | |
| "logits_mup_width_multiplier": 24.0, | |
| "final_logit_softcapping": null, | |
| "swa_head_dim": 128, | |
| "swa_num_attention_heads": 64, | |
| "swa_num_key_value_heads": 16, | |
| "sliding_window_size": 512, | |
| "n_routed_experts": 256, | |
| "num_experts_per_tok": 6, | |
| "n_shared_experts": 2, | |
| "shared_expert_sink": true, | |
| "dense_intermediate_size": 24576, | |
| "intermediate_size": 3072, | |
| "route_scale": 8.0, | |
| "use_gate_bias": true, | |
| "gate_activation": "sigmoid", | |
| "norm_after_topk": true, | |
| "use_global_scale": true | |
| }, | |
| "audio_config": { | |
| "decoder_dmodel": 6144, | |
| "n_mel_bins": 80, | |
| "mel_vocab_size": 16, | |
| "bias": false, | |
| "dmel_min_value": -7.0, | |
| "dmel_max_value": 2.0, | |
| "use_audio_norm": true, | |
| "audio_mode": "dmel" | |
| }, | |
| "vision_config": { | |
| "vision_encoder_type": "hmlp", | |
| "decoder_dmodel": 6144, | |
| "patch_size": 40, | |
| "temporal_patch_size": 2, | |
| "n_channels": 3, | |
| "n_layers": 4, | |
| "use_vision_norm": true | |
| }, | |
| "mtp_config": { | |
| "num_nextn_predict_layers": 8, | |
| "chain_hidden_post_norm": false, | |
| "local_layer_ids": [ | |
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| ] | |
| }, | |
| "quantization": { | |
| "group_size": 64, | |
| "bits": 4, | |
| "recipe": "uniform" | |
| } | |
| } |