LLaMA-Factory

LLaMA-Factory

hoshi-hiyouga
Lens

Lens

Moondream
+
+

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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

Lens is Moondream’s official fine-tuning service, designed to turn a general vision-language model into a highly specialized system tailored to a specific task. It provides a simple, structured workflow where users start by collecting a small dataset of images relevant to their use case, then fine-tune the model through an API using techniques such as supervised fine-tuning (SFT) or reinforcement learning, and finally deploy the customized model either through the cloud or locally with Photon. It is built around the idea that Moondream begins as a general model trained on broad, public data, and fine-tuning adapts it to understand the exact products, documents, categories, or internal information that matter to a business, significantly improving accuracy and reliability for that domain. Lens is designed for production scenarios where performance matters, enabling teams to achieve large gains in accuracy with minimal data by teaching the model to master a defined task.

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

Computer vision teams and AI engineers who need to fine-tune vision models for specific tasks and deploy them with high accuracy in real-world production environments

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

$300 per month
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

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

Review this Software

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

Moondream
Founded: 2024
United States
moondream.ai/p/lens

Alternatives

Alternatives

LLaMA-Factory

LLaMA-Factory

hoshi-hiyouga
Lens

Lens

Moondream

Categories

Categories

Integrations

ChatGLM
DeepSeek
Gemma
LLaVA
Llama
Llama 3
MLflow
Mistral AI
Mixtral 8x22B
Mixtral 8x7B
Moondream
OpenAI
PaliGemma 2
Phi-2
Photon
Qwen
TensorBoard
TensorWave
Yi-Large

Integrations

ChatGLM
DeepSeek
Gemma
LLaVA
Llama
Llama 3
MLflow
Mistral AI
Mixtral 8x22B
Mixtral 8x7B
Moondream
OpenAI
PaliGemma 2
Phi-2
Photon
Qwen
TensorBoard
TensorWave
Yi-Large
Claim LLaMA-Factory and update features and information
Claim LLaMA-Factory and update features and information
Claim Lens and update features and information
Claim Lens and update features and information