Ultra-lightweight 135M instruct model from Hugging Face. Apache 2.0. Optimized for browser/mobile edge deployment, classification, and low-latency fallback tasks.
Alibaba Qwen3.5 sub-1B multimodal model. Text+image+video understanding with 262K context. Apache 2.0. Built for lightweight agentic assistants.
Hugging Face SmolLM2 fine-tuned via Unsloth. 1.7B params, Apache 2.0. Optimized for instruction-following agents in data labeling, product cataloging, and editorial generation.
sweelol/mini-llama-chat
A compact chat-tuned model, distilled from LLaMA-2 for quick interactions.
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 = "sweelol/mini-llama-chat"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
# Your inference code here...meta-llama/Llama-2-13b-chat-hf
Knowledge Distillation (Logits)
Flickr30k (Conceptual)
Multimodal Generation
| Metric | Student Model | Teacher Model |
|---|---|---|
| Model Size | 2.1GB | 8.5GB |
| BLEU Score | 28.5 | 30.1 |