Instructions to use n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit 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("n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit")
config = load_config("n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit")

# 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

How to use n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit"

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": "n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit 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 "n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit"

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 n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit

Run Hermes

hermes

OpenClaw new

How to use n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit"

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 "n0kovo/llama-joycaption-beta-one-hf-llava-mlx-8Bit" \
  --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"

llama-joycaption-beta-one-hf-llava-mlx-8Bit / config.json

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	{
	"architectures": [
	"LlavaForConditionalGeneration"
	],
	"image_seq_length": 729,
	"image_token_index": 128077,
	"model_type": "llava",
	"multimodal_projector_bias": true,
	"projector_hidden_act": "gelu",
	"quantization": {
	"group_size": 64,
	"bits": 8,
	"mode": "affine"
	},
	"quantization_config": {
	"group_size": 64,
	"bits": 8,
	"mode": "affine"
	},
	"text_config": {
	"_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
	"architectures": [
	"LlamaForCausalLM"
	],
	"attention_bias": false,
	"attention_dropout": 0.0,
	"bos_token_id": 128000,
	"eos_token_id": [
	128001,
	128008,
	128009
	],
	"head_dim": 128,
	"hidden_act": "silu",
	"hidden_size": 4096,
	"initializer_range": 0.02,
	"intermediate_size": 14336,
	"max_position_embeddings": 131072,
	"mlp_bias": false,
	"model_type": "llama",
	"num_attention_heads": 32,
	"num_hidden_layers": 32,
	"num_key_value_heads": 8,
	"pretraining_tp": 1,
	"rms_norm_eps": 1e-05,
	"rope_scaling": {
	"factor": 8.0,
	"high_freq_factor": 4.0,
	"low_freq_factor": 1.0,
	"original_max_position_embeddings": 8192,
	"rope_type": "llama3"
	},
	"rope_theta": 500000.0,
	"torch_dtype": "bfloat16",
	"use_cache": true,
	"vocab_size": 128256,
	"tie_word_embeddings": false
	},
	"torch_dtype": "bfloat16",
	"transformers_version": "4.51.0.dev0",
	"vision_feature_layer": -2,
	"vision_feature_select_strategy": "full"
	}