LFM2-VL-450M
16.1K
146
1 language
—
by
LiquidAI
Image Model
OTHER
Fair
16K downloads
Community-tested
Edge AI:
Mobile
Laptop
Server
Unknown
Mobile
Laptop
Server
Quick Summary
LFM2‑VL is Liquid AI's first series of multimodal models, designed to process text and images with variable resolutions.
Training Data Analysis
🔵 Good (6.0/10)
Researched training datasets used by LFM2-VL-450M with quality assessment
Specialized For
general
multilingual
Training Datasets (1)
c4
🔵 6/10
general
multilingual
Key Strengths
- •Scale and Accessibility: 750GB of publicly available, filtered text
- •Systematic Filtering: Documented heuristics enable reproducibility
- •Language Diversity: Despite English-only, captures diverse writing styles
Considerations
- •English-Only: Limits multilingual applications
- •Filtering Limitations: Offensive content and low-quality text remain despite filtering
Explore our comprehensive training dataset analysis
View All DatasetsCode Examples
Load model and processorpythontransformers
from transformers import AutoProcessor, AutoModelForImageTextToText
from transformers.image_utils import load_image
# Load model and processor
model_id = "LiquidAI/LFM2-VL-450M"
model = AutoModelForImageTextToText.from_pretrained(
model_id,
device_map="auto",
dtype="bfloat16"
)
processor = AutoProcessor.from_pretrained(model_id)
# Load image and create conversation
url = "https://www.ilankelman.org/stopsigns/australia.jpg"
image = load_image(url)
conversation = [
{
"role": "user",
"content": [
{"type": "image", "image": image},
{"type": "text", "text": "What is in this image?"},
],
},
]
# Generate Answer
inputs = processor.apply_chat_template(
conversation,
add_generation_prompt=True,
return_tensors="pt",
return_dict=True,
tokenize=True,
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=64)
processor.batch_decode(outputs, skip_special_tokens=True)[0]
# This image depicts a vibrant street scene in what appears to be a Chinatown or similar cultural area. The focal point is a large red stop sign with white lettering, mounted on a pole.Deploy This Model
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