Instructions to use webbrain-one/lfm3-vld-2b-multipass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use webbrain-one/lfm3-vld-2b-multipass with Transformers:

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

pipe = pipeline("image-text-to-text", model="webbrain-one/lfm3-vld-2b-multipass", 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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForImageTextToText
model = AutoModelForImageTextToText.from_pretrained("webbrain-one/lfm3-vld-2b-multipass", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use webbrain-one/lfm3-vld-2b-multipass with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "webbrain-one/lfm3-vld-2b-multipass"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "webbrain-one/lfm3-vld-2b-multipass",
		"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/webbrain-one/lfm3-vld-2b-multipass

SGLang

How to use webbrain-one/lfm3-vld-2b-multipass 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 "webbrain-one/lfm3-vld-2b-multipass" \
    --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": "webbrain-one/lfm3-vld-2b-multipass",
		"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 "webbrain-one/lfm3-vld-2b-multipass" \
        --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": "webbrain-one/lfm3-vld-2b-multipass",
		"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 webbrain-one/lfm3-vld-2b-multipass with Docker Model Runner:
```
docker model run hf.co/webbrain-one/lfm3-vld-2b-multipass
```

lfm3-vld-2b-multipass / README.md

webbrain-one

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---
license: other
license_name: lfm1.0
base_model: LiquidAI/LFM3-VL-2B
pipeline_tag: image-text-to-text
library_name: transformers
tags:
- webbrain
- liquid
- lfm3
- lfm3-vl
- browser-agent
- decision-model
- webbrain-vld
- custom_code
---
# LFM3-VL-2B-VLD Multipass

`LiquidAI/LFM3-VL-2B` adapted with WebBrain's multipass **VL-D** (`verify` Yes/No per option + `readout` option code) decision protocol, distilled from `LiquidAI/d1-2B` on WebBrain multimodal browser workflow screenshots — **without full VL/Compass fine-tuning** (vision tower frozen, language backbone adapted via LoRA and merged to BF16).

## Companion Repositories

- [`webbrain-one/lfm3-vld-2b-multipass-onnx`](https://huggingface.co/webbrain-one/lfm3-vl-2b-vld-onnx): WebGPU ONNX bundle (`decoder_q8f16.onnx`, `decoder_q4f16.onnx` with `decision_hidden` exposed, `vision_encoder_fp16.onnx`, and trained linear decision probes).
- [`webbrain-one/lfm3-vld-2b-multipass-gguf`](https://huggingface.co/webbrain-one/lfm3-vl-2b-vld-gguf): GGUF exports (`BF16`, `Q8_0`, `Q4_K_M`, and `mmproj-F16`) for `llama.cpp` (`/v1/chat/completions` + `/v1/systemone`).
- [`webbrain-one/lfm3-vld-2b-multipass-lora`](https://huggingface.co/webbrain-one/lfm3-vl-2b-vld-lora): LoRA adapter (`r=32, alpha=64`) and projector weights.

## Results on d1 Balanced Browser Decision Benchmark (`final_test`, 126 Categorical Questions)
| Model / Protocol | Correct | Completions Found | False Completions | Unknown Recognized | Score MAE |
|---|---:|---:|---:|---:|---:|
| **LFM3-VLD-2B (`probe` / `probe-cs`)** | **126/126 (100.0%)** | **24/24** | **0/48** | **24/24** | **9.56e-8** |
| **LFM3-VLD-2B (`verify` zero-shot)** | **126/126 (100.0%)** | **24/24** | **0/48** | **24/24** | **4.11e-5** |
| **LFM3-VLD-2B (`readout`)** | **125/126 (99.2%)** | **24/24** | **0/48** | **24/24** | **0.0189** |
| Base `LiquidAI/LFM3-VL-2B` (`verify` zero-shot) | 106/126 (84.1%) | 24/24 | 0/48 | 4/24 | 0.0004 |
| Base `LiquidAI/LFM3-VL-2B` (`readout`) | 102/126 (81.0%) | 24/24 | 1/48 | 0/24 | 0.1106 |

	---
	license: other
	license_name: lfm1.0
	base_model: LiquidAI/LFM3-VL-2B
	pipeline_tag: image-text-to-text
	library_name: transformers
	tags:
	- webbrain
	- liquid
	- lfm3
	- lfm3-vl
	- browser-agent
	- decision-model
	- webbrain-vld
	- custom_code
	---

	# LFM3-VL-2B-VLD Multipass

	`LiquidAI/LFM3-VL-2B` adapted with WebBrain's multipass VL-D (`verify` Yes/No per option + `readout` option code) decision protocol, distilled from `LiquidAI/d1-2B` on WebBrain multimodal browser workflow screenshots — without full VL/Compass fine-tuning (vision tower frozen, language backbone adapted via LoRA and merged to BF16).

	## Companion Repositories

	- [`webbrain-one/lfm3-vld-2b-multipass-onnx`](https://huggingface.co/webbrain-one/lfm3-vl-2b-vld-onnx): WebGPU ONNX bundle (`decoder_q8f16.onnx`, `decoder_q4f16.onnx` with `decision_hidden` exposed, `vision_encoder_fp16.onnx`, and trained linear decision probes).
	- [`webbrain-one/lfm3-vld-2b-multipass-gguf`](https://huggingface.co/webbrain-one/lfm3-vl-2b-vld-gguf): GGUF exports (`BF16`, `Q8_0`, `Q4_K_M`, and `mmproj-F16`) for `llama.cpp` (`/v1/chat/completions` + `/v1/systemone`).
	- [`webbrain-one/lfm3-vld-2b-multipass-lora`](https://huggingface.co/webbrain-one/lfm3-vl-2b-vld-lora): LoRA adapter (`r=32, alpha=64`) and projector weights.

	## Results on d1 Balanced Browser Decision Benchmark (`final_test`, 126 Categorical Questions)

	\| Model / Protocol \| Correct \| Completions Found \| False Completions \| Unknown Recognized \| Score MAE \|
	\|---\|---:\|---:\|---:\|---:\|---:\|
	\| LFM3-VLD-2B (`probe` / `probe-cs`) \| 126/126 (100.0%) \| 24/24 \| 0/48 \| 24/24 \| 9.56e-8 \|
	\| LFM3-VLD-2B (`verify` zero-shot) \| 126/126 (100.0%) \| 24/24 \| 0/48 \| 24/24 \| 4.11e-5 \|
	\| LFM3-VLD-2B (`readout`) \| 125/126 (99.2%) \| 24/24 \| 0/48 \| 24/24 \| 0.0189 \|
	\| Base `LiquidAI/LFM3-VL-2B` (`verify` zero-shot) \| 106/126 (84.1%) \| 24/24 \| 0/48 \| 4/24 \| 0.0004 \|
	\| Base `LiquidAI/LFM3-VL-2B` (`readout`) \| 102/126 (81.0%) \| 24/24 \| 1/48 \| 0/24 \| 0.1106 \|