SmolLM
Hugging Face TB small LM family (135M–1.7B) with Apache-2.0 weights aimed at on-device and edge quality per size.
Why it is included
Modern permissive tiny models with HF-native tooling and benchmarks.
Best for
Edge demos, mobile prototypes, and teaching efficient LM design.
Strengths
- Tiny
- Apache-2
- HF integration
Limitations
- Capability vs 7B+ for hard tasks
Good alternatives
TinyLlama · Phi · Gemma
Related tools
AI & Machine Learning
TinyLlama
1.1B-parameter Llama-architecture model trained on ~3T tokens—Apache-2.0 weights for fast experiments and teaching.
AI & Machine Learning
Hugging Face Transformers
State-of-the-art pretrained models for PyTorch, TensorFlow, and JAX.
AI & Machine Learning
Microsoft Phi
Small language model family (Phi-3/4 lineage) emphasizing strong quality per parameter; weights on Hugging Face under Microsoft licenses per release.
AI & Machine Learning
MLC LLM
Universal deployment stack compiling models to Vulkan, Metal, CUDA, and WebGPU via TVM/Unity for phones, browsers, and servers.
AI & Machine Learning
Axolotl
YAML-configured fine-tuning for LLMs: LoRA, QLoRA, FSDP, and many architectures on top of Hugging Face trainers.
AI & Machine Learning
Google Gemma
Google’s smaller open **weights** Gemma line (Gemma 2/3, etc.) with Gemma license terms, plus `gemma.cpp` for lightweight CPU inference.