Instructions to use mlx-community/LFM2-VL-1.6B-5bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlx-community/LFM2-VL-1.6B-5bit with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="mlx-community/LFM2-VL-1.6B-5bit", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModelForImageTextToText
model = AutoModelForImageTextToText.from_pretrained("mlx-community/LFM2-VL-1.6B-5bit", trust_remote_code=True, dtype="auto")

MLX

How to use mlx-community/LFM2-VL-1.6B-5bit 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("mlx-community/LFM2-VL-1.6B-5bit")
config = load_config("mlx-community/LFM2-VL-1.6B-5bit")

# 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
LM Studio

vLLM

How to use mlx-community/LFM2-VL-1.6B-5bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mlx-community/LFM2-VL-1.6B-5bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlx-community/LFM2-VL-1.6B-5bit",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/mlx-community/LFM2-VL-1.6B-5bit

SGLang

How to use mlx-community/LFM2-VL-1.6B-5bit with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mlx-community/LFM2-VL-1.6B-5bit" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlx-community/LFM2-VL-1.6B-5bit",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mlx-community/LFM2-VL-1.6B-5bit" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mlx-community/LFM2-VL-1.6B-5bit",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use mlx-community/LFM2-VL-1.6B-5bit with Docker Model Runner:
```
docker model run hf.co/mlx-community/LFM2-VL-1.6B-5bit
```

LFM2-VL-1.6B-5bit / config.json

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	{
	"add_cross_attention": false,
	"architectures": [
	"Lfm2VlForConditionalGeneration"
	],
	"auto_map": {
	"AutoConfig": "modeling_lfm2_vl.Lfm2VlConfig",
	"AutoModelForImageTextToText": "modeling_lfm2_vl.Lfm2VlForConditionalGeneration"
	},
	"bad_words_ids": null,
	"begin_suppress_tokens": null,
	"bos_token_id": null,
	"chunk_size_feed_forward": 0,
	"cross_attention_hidden_size": null,
	"decoder_start_token_id": null,
	"diversity_penalty": 0.0,
	"do_image_splitting": true,
	"do_sample": false,
	"downsample_factor": 2,
	"early_stopping": false,
	"encoder_no_repeat_ngram_size": 0,
	"encoder_patch_size": 16,
	"eos_token_id": null,
	"exponential_decay_length_penalty": null,
	"finetuning_task": null,
	"forced_bos_token_id": null,
	"forced_eos_token_id": null,
	"id2label": {
	"0": "LABEL_0",
	"1": "LABEL_1"
	},
	"image_token_index": 396,
	"is_decoder": false,
	"is_encoder_decoder": false,
	"label2id": {
	"LABEL_0": 0,
	"LABEL_1": 1
	},
	"length_penalty": 1.0,
	"max_image_tokens": 256,
	"max_length": 20,
	"max_num_patches": 1024,
	"max_pixels_tolerance": 1.5,
	"max_tiles": 10,
	"min_image_tokens": 64,
	"min_length": 0,
	"min_tiles": 2,
	"model_type": "lfm2-vl",
	"no_repeat_ngram_size": 0,
	"num_beam_groups": 1,
	"num_beams": 1,
	"num_return_sequences": 1,
	"output_attentions": false,
	"output_hidden_states": false,
	"output_scores": false,
	"pad_token_id": null,
	"prefix": null,
	"problem_type": null,
	"projector_bias": true,
	"projector_hidden_act": "gelu",
	"projector_hidden_size": 2560,
	"pruned_heads": {},
	"quantization": {
	"group_size": 64,
	"bits": 5
	},
	"quantization_config": {
	"group_size": 64,
	"bits": 5
	},
	"remove_invalid_values": false,
	"repetition_penalty": 1.0,
	"return_dict": true,
	"return_dict_in_generate": false,
	"sep_token_id": null,
	"suppress_tokens": null,
	"task_specific_params": null,
	"temperature": 1.0,
	"text_config": {
	"vocab_size": 65536,
	"hidden_size": 2048,
	"num_hidden_layers": 16,
	"rope_theta": 1000000.0,
	"max_position_embeddings": 128000,
	"use_cache": true,
	"norm_eps": 1e-05,
	"initializer_range": 0.02,
	"num_attention_heads": 32,
	"num_key_value_heads": 8,
	"conv_bias": false,
	"conv_L_cache": 3,
	"intermediate_size": 12288,
	"block_multiple_of": 256,
	"block_ffn_dim_multiplier": 1.0,
	"block_auto_adjust_ff_dim": true,
	"layer_types": [
	"conv",
	"conv",
	"full_attention",
	"conv",
	"conv",
	"full_attention",
	"conv",
	"conv",
	"full_attention",
	"conv",
	"full_attention",
	"conv",
	"full_attention",
	"conv",
	"full_attention",
	"conv"
	],
	"return_dict": true,
	"output_hidden_states": false,
	"torchscript": false,
	"torch_dtype": "bfloat16",
	"pruned_heads": {},
	"tie_word_embeddings": true,
	"chunk_size_feed_forward": 0,
	"is_encoder_decoder": false,
	"is_decoder": false,
	"cross_attention_hidden_size": null,
	"add_cross_attention": false,
	"tie_encoder_decoder": false,
	"architectures": [
	"Lfm2ForCausalLM"
	],
	"finetuning_task": null,
	"id2label": {
	"0": "LABEL_0",
	"1": "LABEL_1"
	},
	"label2id": {
	"LABEL_0": 0,
	"LABEL_1": 1
	},
	"task_specific_params": null,
	"problem_type": null,
	"tokenizer_class": null,
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	"bos_token_id": 1,
	"pad_token_id": 0,
	"eos_token_id": 7,
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	"max_length": 20,
	"min_length": 0,
	"do_sample": false,
	"early_stopping": false,
	"num_beams": 1,
	"num_beam_groups": 1,
	"diversity_penalty": 0.0,
	"temperature": 1.0,
	"top_k": 50,
	"top_p": 1.0,
	"typical_p": 1.0,
	"repetition_penalty": 1.0,
	"length_penalty": 1.0,
	"no_repeat_ngram_size": 0,
	"encoder_no_repeat_ngram_size": 0,
	"bad_words_ids": null,
	"num_return_sequences": 1,
	"output_scores": false,
	"return_dict_in_generate": false,
	"forced_bos_token_id": null,
	"forced_eos_token_id": null,
	"remove_invalid_values": false,
	"exponential_decay_length_penalty": null,
	"suppress_tokens": null,
	"begin_suppress_tokens": null,
	"_name_or_path": "LiquidAI/LFM2-1.2B",
	"block_dim": 2048,
	"block_ff_dim": 12288,
	"block_mlp_init_scale": 1.0,
	"block_norm_eps": 1e-05,
	"block_out_init_scale": 1.0,
	"block_use_swiglu": true,
	"block_use_xavier_init": true,
	"conv_dim": 2048,
	"conv_dim_out": 2048,
	"conv_use_xavier_init": true,
	"model_type": "lfm2",
	"num_heads": 32,
	"use_pos_enc": true,
	"tf_legacy_loss": false,
	"use_bfloat16": false,
	"output_attentions": false
	},
	"tf_legacy_loss": false,
	"tie_encoder_decoder": false,
	"tie_word_embeddings": true,
	"tile_size": 512,
	"tokenizer_class": null,
	"top_k": 50,
	"top_p": 1.0,
	"torchscript": false,
	"transformers_version": "4.55.0",
	"typical_p": 1.0,
	"use_bfloat16": false,
	"use_image_special_tokens": true,
	"use_thumbnail": true,
	"vision_config": {
	"return_dict": true,
	"output_hidden_states": false,
	"torchscript": false,
	"torch_dtype": "bfloat16",
	"pruned_heads": {},
	"tie_word_embeddings": true,
	"chunk_size_feed_forward": 0,
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	"add_cross_attention": false,
	"tie_encoder_decoder": false,
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	"finetuning_task": null,
	"id2label": {
	"0": "LABEL_0",
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	},
	"label2id": {
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	"LABEL_1": 1
	},
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	"problem_type": null,
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	"decoder_start_token_id": null,
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	"min_length": 0,
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	"num_beam_groups": 1,
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	"temperature": 1.0,
	"top_k": 50,
	"top_p": 1.0,
	"typical_p": 1.0,
	"repetition_penalty": 1.0,
	"length_penalty": 1.0,
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	"encoder_no_repeat_ngram_size": 0,
	"bad_words_ids": null,
	"num_return_sequences": 1,
	"output_scores": false,
	"return_dict_in_generate": false,
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	"forced_eos_token_id": null,
	"remove_invalid_values": false,
	"exponential_decay_length_penalty": null,
	"suppress_tokens": null,
	"begin_suppress_tokens": null,
	"_name_or_path": "",
	"model_type": "siglip2_vision_model",
	"vision_use_head": false,
	"tf_legacy_loss": false,
	"use_bfloat16": false,
	"hidden_size": 1152,
	"intermediate_size": 4304,
	"num_hidden_layers": 27,
	"num_attention_heads": 16,
	"num_channels": 3,
	"patch_size": 16,
	"attention_dropout": 0.0,
	"layer_norm_eps": 1e-06,
	"hidden_act": "gelu_pytorch_tanh",
	"num_patches": 256,
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	},
	"vision_feature_layer": -2
	}