unsloth/LFM2-700M-GGUF
NewLiquid AI hybrid architecture via Unsloth. 700M params, 32K context, CPU-optimized. Built for narrow-scope agentic tasks: data extraction, RAG, multi-turn workflows.
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How to Use
To get started, install the `transformers` library:
pip install transformersThen, use the following snippet to load the model:
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "mistralai/Ministral-3-3B-Instruct-GGUF"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
# Your inference code here...Available Versions
Model Details
Teacher Model
Ministral-8B
Distillation Method
Knowledge Distillation (Logits)
Training Dataset
Flickr30k (Conceptual)
Primary Task
Multimodal Generation
Performance Metrics (Example)
| Metric | Student Model | Teacher Model |
|---|---|---|
| Model Size | 2.9GB | 8.5GB |
| BLEU Score | 28.5 | 30.1 |