jzhang38/TinyLlama resource

Health v2 · maintenance only

Flags: no_releases archived

Adoption not part of the score

9019 stars · 630 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

TinyLlama is an open-source project that pretrained a compact 1.1B-parameter Llama 2 architecture model on 3 trillion tokens, releasing checkpoints and training details. It includes evaluation results, fine-tuning scripts, and examples such as speculative decoding with llama.cpp.

Use cases

• pretrain a small Llama-compatible language model
• run a compact LLM on limited compute or memory
• fine-tune a small base model for chat
• use a Llama 2 drop-in replacement with fewer parameters
• study intermediate checkpoints of an open LLM pretraining run
• speed up inference with speculative decoding

When to choose

• you need a small, Llama 2-compatible model for resource-constrained environments
• you want an open base model to fine-tune cheaply
• you want to study or reproduce an open pretraining effort

When to avoid

• you need state-of-the-art reasoning or broad knowledge from a larger model
• you want a ready-made production assistant rather than a base model
• you cannot host or fine-tune models yourself

Facets

learning-resource · maturity stable

llm-training machine-learning deep-learning large-language-models deep-learning machine-learning python tinyllama llama-2 pretraining small-language-model open-source-model checkpoints speculative-decoding gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="jzhang38/TinyLlama")