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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Axolotl is an innovative open-source tool crafted to enhance the fine-tuning process of a variety of AI models, accommodating numerous configurations and architectures. This platform empowers users to train models using diverse methods such as full fine-tuning, LoRA, QLoRA, ReLoRA, and GPTQ. Additionally, users have the flexibility to customize their configurations through straightforward YAML files or by employing command-line interface overrides, while also being able to load datasets in various formats, whether custom or pre-tokenized. Axolotl seamlessly integrates with cutting-edge technologies, including xFormers, Flash Attention, Liger kernel, RoPE scaling, and multipacking, and it is capable of operating on single or multiple GPUs using Fully Sharded Data Parallel (FSDP) or DeepSpeed. Whether run locally or in the cloud via Docker, it offers robust support for logging results and saving checkpoints to multiple platforms, ensuring users can easily track their progress. Ultimately, Axolotl aims to make the fine-tuning of AI models not only efficient but also enjoyable, all while maintaining a high level of functionality and scalability. With its user-friendly design, it invites both novices and experienced practitioners to explore the depths of AI model training.

Description

LLaMA-Factory is an innovative open-source platform aimed at simplifying and improving the fine-tuning process for more than 100 Large Language Models (LLMs) and Vision-Language Models (VLMs). It accommodates a variety of fine-tuning methods such as Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and Prefix-Tuning, empowering users to personalize models with ease. The platform has shown remarkable performance enhancements; for example, its LoRA tuning achieves training speeds that are up to 3.7 times faster along with superior Rouge scores in advertising text generation tasks when compared to conventional techniques. Built with flexibility in mind, LLaMA-Factory's architecture supports an extensive array of model types and configurations. Users can seamlessly integrate their datasets and make use of the platform’s tools for optimized fine-tuning outcomes. Comprehensive documentation and a variety of examples are available to guide users through the fine-tuning process with confidence. Additionally, this platform encourages collaboration and sharing of techniques among the community, fostering an environment of continuous improvement and innovation.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Llama Yes 
MLflow Yes 
Mistral AI Yes 
Phi-2 Yes 
Qwen Yes 
TensorWave Yes 
Docker Yes 
Falcon Yes 
GPT-J Yes 
Gemma No 
Hugging Face Yes 
LLaVA No 
MPT-7B Yes 
Mixtral 8x22B No 
Mixtral 8x7B No 
OpenAI No 
OpenPipe Yes 
TensorBoard No 
Weights & Biases Yes 
XGen Security Yes 

Integrations

Llama Yes 
MLflow Yes 
Mistral AI Yes 
Phi-2 Yes 
Qwen Yes 
TensorWave Yes 
Docker No 
Falcon No 
GPT-J No 
Gemma Yes 
Hugging Face No 
LLaVA Yes 
MPT-7B No 
Mixtral 8x22B Yes 
Mixtral 8x7B Yes 
OpenAI Yes 
OpenPipe No 
TensorBoard Yes 
Weights & Biases No 
XGen Security No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Axolotl

Country

United States

Website

axolotl.ai/

Vendor Details

Company Name

hoshi-hiyouga

Website

github.com/hiyouga/LLaMA-Factory

Product Features

Product Features

Alternatives

Alternatives

LLaMA-Factory Reviews

LLaMA-Factory

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