LLaMA-Factory

LLaMA-Factory

hoshi-hiyouga
Tinker

Tinker

Thinking Machines Lab
+
+

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About

​LLaMA-Factory is an open source platform designed to streamline and enhance the fine-tuning process of over 100 Large Language Models (LLMs) and Vision-Language Models (VLMs). It supports various fine-tuning techniques, including Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and Prefix-Tuning, allowing users to customize models efficiently. It has demonstrated significant performance improvements; for instance, its LoRA tuning offers up to 3.7 times faster training speeds with better Rouge scores on advertising text generation tasks compared to traditional methods. LLaMA-Factory's architecture is designed for flexibility, supporting a wide range of model architectures and configurations. Users can easily integrate their datasets and utilize the platform's tools to achieve optimized fine-tuning results. Detailed documentation and diverse examples are provided to assist users in navigating the fine-tuning process effectively.

About

Tinker is a training API designed for researchers and developers that allows full control over model fine-tuning while abstracting away the infrastructure complexity. It supports primitives and enables users to build custom training loops, supervision logic, and reinforcement learning flows. It currently supports LoRA fine-tuning on open-weight models across both LLama and Qwen families, ranging from small models to large mixture-of-experts architectures. Users write Python code to handle data, loss functions, and algorithmic logic; Tinker handles scheduling, resource allocation, distributed training, and failure recovery behind the scenes. The service lets users download model weights at different checkpoints and doesn’t force them to manage the compute environment. Tinker is delivered as a managed offering; training jobs run on Thinking Machines’ internal GPU infrastructure, freeing users from cluster orchestration.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

AI researchers and developers wanting a solution to fine-tune a wide array of language and vision-language models

Audience

AI researchers and ML engineers requiring a solution to experiment with fine-tuning open source language models while outsourcing infrastructure complexity

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

hoshi-hiyouga
github.com/hiyouga/LLaMA-Factory

Company Information

Thinking Machines Lab
United States
thinkingmachines.ai/tinker/

Alternatives

Alternatives

Tinker

Tinker

Thinking Machines Lab
LLaMA-Factory

LLaMA-Factory

hoshi-hiyouga

Categories

Categories

Integrations

Llama 3
Qwen
ChatGLM
DeepSeek
Gemma
Llama
Llama 3.1
Llama 3.2
Llama 3.3
MLflow
Mistral AI
Mixtral 8x22B
Mixtral 8x7B
OpenAI
PaliGemma 2
Phi-2
Python
Qwen3
TensorBoard
TensorWave

Integrations

Llama 3
Qwen
ChatGLM
DeepSeek
Gemma
Llama
Llama 3.1
Llama 3.2
Llama 3.3
MLflow
Mistral AI
Mixtral 8x22B
Mixtral 8x7B
OpenAI
PaliGemma 2
Phi-2
Python
Qwen3
TensorBoard
TensorWave
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