OpenCoder-llm/OpenCoder-llm resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2111 stars · 126 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OpenCoder is a fully open and reproducible family of code large language models (1.5B and 8B base and chat variants) trained on 2.5 trillion tokens, released with model weights, training data, data processing pipelines, and evaluation frameworks. The repository serves as the central hub ('open cookbook') for the models, the RefineCode pretraining corpus, SFT datasets, intermediate checkpoints, and the OpenCodeEval evaluation framework.

Use cases

• train a code large language model from scratch
• download open code llm weights for code generation
• build a reproducible code pretraining corpus
• evaluate code llms on benchmarks like humaneval
• study ablation results for code llm training strategies
• fine-tune a code model with open sft datasets
• clean and filter code data for pretraining

When to choose

• you need a fully open, reproducible code LLM with transparent data pipeline
• you want to reproduce or extend top-tier code model training
• you need an efficient evaluation framework for code generation models
• you want high-quality open code pretraining and SFT datasets

When to avoid

• you just need a hosted code assistant without training infrastructure
• you need the largest closed models like GPT-4 or Claude for coding
• you lack GPU resources for running or training multi-billion parameter models
• you need a production inference server rather than research artifacts

Facets

learning-resource · maturity active

llm-training llm-inference machine-learning etl benchmarking data-generation large-language-models machine-learning deep-learning developer-tools python cross-platform code-llm open-weights pretraining refinecode opencodereval huggingface reproducible-research sft-dataset data-engineering gpu linux

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markdown · JSON · MCP: product_card(name="OpenCoder-llm/OpenCoder-llm")