LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Quickly check LlamaFactory model support status. Inspect the SUPPORTED_MODELS registry in constants.py for a full list of compatible architectures.
How LlamaFactory Integrates with Experiment Tracking Tools: A Complete Technical GuideDiscover how LlamaFactory integrates with experiment tracking tools. Learn to route metrics and hyperparameters effortlessly for better ML model development with our technical guide.
Key Files for Configuring LlamaFactory: CLI, YAML, and Web UI ReferenceMaster LlamaFactory configuration with this guide. Discover key files for CLI, YAML, and Web UI setup, including parser.py and common.py. Optimize your LlamaFactory projects today.
How LlamaFactory Handles Large Datasets Using Streaming Mode: A Complete Technical GuideDiscover how LlamaFactory handles large datasets with streaming mode. Learn to train on massive corpora without loading everything into RAM. A complete technical guide.
Efficiency Techniques Implemented in LlamaFactory's Model Layer: A Complete Optimization GuideDiscover LlamaFactory's model layer efficiency techniques. Fine-tune 70B models on consumer hardware with gradient checkpointing, 4-bit quantization, GaLore, and more. Optimize GPU memory up to 75%.
What Quantization Methods Are Supported by LlamaFactory? A Complete Guide to 9 TechniquesExplore LlamaFactory's comprehensive support for nine quantization methods like BNB GPTQ AWQ and more. Discover runtime and post-training techniques for efficient model deployment.
Does LlamaFactory Offer Zero-Code Training? A Complete Technical GuideDiscover if LlamaFactory offers zero-code training. This technical guide explains how to fine-tune 100+ LLMs using YAML and a simple CLI or web UI without writing Python code.
What is LlamaBoard and How Does It Work: The Complete Guide to LlamaFactory's Web UIDiscover LlamaBoard, the Gradio web UI for LlamaFactory. Easily configure, launch, and monitor LLM fine-tuning jobs via your browser. No Python code needed.
How to Use the OpenAI-Compatible API Provided by LlamaFactoryLearn how to use LlamaFactory's OpenAI-compatible API. Connect any model to standard OpenAI SDKs by changing the base URL and leverage powerful LLMs with ease.
LlamaFactory Inference Backends: The Complete Guide to Engine SelectionExplore LlamaFactory inference backends including HuggingFace Transformers vLLM SGLang and K-Transformers. Optimize your LLM deployment by selecting the best engine.
Inference Capabilities of LlamaFactory: A Complete Guide to vLLM, HuggingFace, and SGLang BackendsExplore LlamaFactory's inference capabilities with vLLM HuggingFace and SGLang backends. Deploy seamlessly across single-GPU multi-GPU and server environments.
How to Enable Distributed Training with LlamaFactory: FSDP, DeepSpeed, and Multi-Node SetupsEasily enable distributed training in LlamaFactory using FSDP, DeepSpeed, or multi-node setups. Configure your YAML and launch with torchrun for efficient model training.
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