Similar Models

LFM2-700M (Edge Agentic)

unsloth/LFM2-700M-GGUF

Liquid AI hybrid architecture via Unsloth. 700M params, 32K context, CPU-optimized. Built for narrow-scope agentic tasks: data extraction, RAG, multi-turn workflows.

How to Use

To get started, install the `transformers` library:

pip install transformers

Then, use the following snippet to load the model:

from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "unsloth/LFM2-700M-GGUF"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

# Your inference code here...

Available Versions

Tag / VariantSizeFormatDownload
unsloth/LFM2-700M-GGUF:Q4_K_M469MBGGUFLink
unsloth/LFM2-700M-GGUF:Q6_K612MBGGUFLink

Model Details

Teacher Model

LFM2-1.2B

Distillation Method

Knowledge Distillation (Logits)

Training Dataset

Flickr30k (Conceptual)

Primary Task

Multimodal Generation

Performance Metrics (Example)

MetricStudent ModelTeacher Model
Model Size469MB8.5GB
BLEU Score28.530.1