MiniGPT2-22M-GGUF

MiniGPT2-22M (GGUF, F16)

A 22M-parameter language model trained from scratch by SmallAICreator / UltraLabs, small enough to chat on a phone.

• File: MiniGPT2-22M-F16.gguf (44.6 MB), for llama.cpp, PocketPal, LM Studio, Ollama, etc.
• Chat template is embedded, so apps pick up the right format automatically.

Model

Prompt format

<|system|>You are a helpful assistant.<|end|><|user|>What is the capital of France?<|end|><|assistant|>

No BOS token. The model ends its turn with <|end|>.

llama-cli -m MiniGPT2-22M-F16.gguf -cnv

Tool calling

The embedded chat template supports tools (OpenAI-style tools / tool_calls), so apps with a tool picker enable it automatically. The model emits:

<tool_call>
{"name": "web_search", "arguments": {"query": "Tokyo weather today"}}
</tool_call>

Tool results go back as a tool message, which the template renders as a <tool_response> turn. The model then answers from the result. It was trained on calculator, web_search, fetch_url, search_knowledge_base and execute_javascript calls. Remember it's 22M, so double-check arguments.

Examples

Who are you? I'm MiniGPT2, a tiny 22M-parameter model from UltraLabs. I'm small, so I get facts wrong and I'm weak at multi-step arithmetic.

What is the capital of France? The capital of France is Paris.

Write a haiku about the ocean. Waves whisper softly / rolling onto quiet sand / the ocean breathes and rests.

Benchmarks

0-shot, lm-evaluation-harness 0.4.13, fp32. Every model was run through the same harness. Our Supra-50M run reproduces that model's published numbers exactly.

MiniGPT2 beats Pythia-70M (3.2x its size) on 6 of 11 tasks and ties BLiMP. It trails Supra-50M, a model 2.3x larger.

Conversion

Converted from the original JAX checkpoint to HF Llama, then to GGUF. Verified:

• The HF model matches the training forward pass (max logit diff 4e-5).
• llama.cpp tokenization matches the HF tokenizer exactly.
• The F16 GGUF's logits match HF (top-1 agreement 100%, mean KL 7.6e-6).

Limitations

This is a 22M model. It makes factual mistakes, is weak at arithmetic and multi-step reasoning, and can be verbose. Do not rely on it for anything important.