LlamaFactory vs Chinese-LLaMA-Alpaca

Common questions

What is the difference between LlamaFactory and Chinese-LLaMA-Alpaca?

LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. Chinese-LLaMA-Alpaca: Chinese LLaMA & Alpaca LLMs. See the comparison table for live GitHub stats and shared categories.

When should I choose LlamaFactory over Chinese-LLaMA-Alpaca?

Choose LlamaFactory over Chinese-LLaMA-Alpaca when Requirements: Min 4 GB RAM; Requires Docker; Hardware requirements vary based on the method and model size. For example, full fine-tuning of a 7B model requires 120GB of memory, while QLoRA with 2-bit can ; Installation is mandatory and can be done from source or via Docker. Additional dependencies like metrics and deepspeed are optional.; For Windows users, manual installation of PyTorch with CUDA support is required, and bitsandbytes must be installed for QLoRA support.; Graph edge: LlamaFactory is a typed related of Chinese-LLaMA-Alpaca - see the relationship row above; Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; Use LlamaFactory when you need to fine-tune a wide range of large language models and vision-language models with methods like LoRA, QLoRA, and quantization.

When should I choose Chinese-LLaMA-Alpaca over LlamaFactory?

Choose Chinese-LLaMA-Alpaca over LlamaFactory when Pricing: The repository provides free access to the models and scripts, but users may incur costs related to hardware and cloud services for deployment.; Requirements: Min 8 GB RAM; Requires Python environment.; Supports deployment on local CPU/GPU.; Graph edge: Chinese-LLaMA-Alpaca is a typed related of LlamaFactory - see the relationship row above; Tags unique to Chinese-LLaMA-Alpaca: alpaca, llm, lora, nlp; Also covers Inference & Serving; When you need Chinese-specific large language models for tasks that require deep understanding of the Chinese language.

When should I avoid LlamaFactory?

Avoid LlamaFactory if you are working with models not included in its supported list of over 100 models, as it may not provide the necessary fine-tuning capabilities. Do not use LlamaFactory if you are working in an environment where Python or specific dependencies like PyTorch and bitsandbytes cannot be installed or are not supported. LlamaFactory may not be suitable if you require real-time or near-real-time fine-tuning capabilities, as the setup and installation process can be complex and time-consuming.

When should I avoid Chinese-LLaMA-Alpaca?

If your project requires models that are not specific to the Chinese language or do not benefit from Chinese-specific pre-training. When you need models that are not available in the sizes provided by Chinese-LLaMA-Alpaca, such as models smaller than 7B or larger than 33B. If you prefer models that are not based on LLaMA or Alpaca architectures.

Is LlamaFactory or Chinese-LLaMA-Alpaca more popular on GitHub?

LlamaFactory has more GitHub stars (74,849 vs 18,943). Stars measure visibility, not whether either tool fits your constraints.

Are LlamaFactory and Chinese-LLaMA-Alpaca open source?

Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, Chinese-LLaMA-Alpaca: Apache-2.0).

Where can I find alternatives to LlamaFactory or Chinese-LLaMA-Alpaca?

GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and Chinese-LLaMA-Alpaca alternatives (LlamaFactory markdown twin, Chinese-LLaMA-Alpaca markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, LlamaFactory or Chinese-LLaMA-Alpaca?

LlamaFactory: Very active. Chinese-LLaMA-Alpaca: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for LlamaFactory and Chinese-LLaMA-Alpaca?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; Chinese-LLaMA-Alpaca trust report.