Best AI tools for< Train Model Weights >

Weights & Biases is a machine learning platform that helps data scientists and engineers build, train, and deploy machine learning models. It provides a central location to track and manage all of your machine learning projects, and it offers a variety of tools to help you collaborate with others and share your work.

CrazyHorseAI is an AI tool that offers an API for users to enhance and customize the appearance and personality traits of an AI girl through features like changing clothes, hair, body, pose, and background. The tool provides functionalities such as natural language processing, emotional intelligence, and adaptive learning capabilities to create immersive and engaging experiences.

Voicemy.ai is an AI application that allows users to create AI voices and songs. Users can clone voices of famous personalities, compose melodies, and convert text into spoken words using chosen voice models. The platform aims to inspire creativity and enable users to share their passion with the world.

Controlla Voice is an AI application that allows users to transform vocals into new voices or instruments, swap any song to their own voice in any language, and create unique blended voices. Users can train their own AI singing voice, generate AI cover songs, and create realistic choirs with customizable harmonies. The application provides a vocal toolkit for never-before-heard sounds and offers flexible pricing options to access high-quality AI singing voices. With Controlla Voice, users can enhance their voice, express themselves in their most natural way, and monetize their music with automatic royalties.

Instashot is an AI application that allows users to generate AI portraits with the highest face resemblance in less than a minute. Users can submit their photos to train a custom AI model, which can then be used to generate portraits with unique prompts. The application offers different pricing tiers with varying features and benefits, making it accessible to a wide range of users. Instashot utilizes Stable Diffusion AI technologies to create portraits that best describe the user, ensuring high-quality results. The application is user-friendly, efficient, and provides a fun way to explore AI-generated art.

Runway is an applied AI research company shaping the next era of art, entertainment, and human creativity. With a suite of creative tools designed to turn ideas into reality, Runway empowers users to explore the possibilities of AI-generated worlds. Founded in 2018, Runway has been pushing creativity forward with cutting-edge research in artificial intelligence and machine learning, collaborating with leading institutes worldwide.

ImagineMe is a personal AI art generator that allows users to create stunning art of themselves from a simple text description. The application uses AI models to convert text into corresponding images, enabling users to visualize themselves in various scenarios. ImagineMe offers an easy, affordable, and magical way to create personalized art.

Quivr is an open-source chat-powered second brain application that transforms private and enterprise knowledge into a personal AI assistant. It continuously learns and improves at every interaction, offering AI-powered workplace search synced with user data. Quivr allows users to connect with their favorite tools, databases, and applications, and configure their 'second brain' to train on their company's unique context for improved search relevance and knowledge discovery.

Pawfect Snapshots is an AI pet photography application that allows users to create personalized and stunning portraits of their pets using advanced AI technology. Users can choose from a variety of artistic styles, sceneries, and times of day to bring out their pet's unique charm. The application provides a seamless process for generating pet portraits, from uploading photos to selecting styles and downloading the final masterpiece. With Pawfect Snapshots, users can immortalize their furry friends in beautiful and creative ways.

SecondSoul is an AI platform that enables users to create their AI clone for engaging 24/7 conversations on Telegram. It allows users to customize their AI clone with unique traits, voice, and train it to mimic their style. The platform offers a straightforward pricing model with a revenue split, where creators earn 80% of the messages fee from users of their clone. SecondSoul aims to enhance user experience, provide companionship, and monetize community interactions through AI technology.

ThumbnailsPro is the #1 YouTube Thumbnails Generator for Viral Videos, offering instant AI-generated thumbnails to increase click-through rates. The AI is trained on thousands of viral videos to ensure optimized thumbnail creation. Users can upload images, enter video titles, and generate multiple thumbnail options in under 30 seconds. With affordable subscription plans, full ownership rights, and a user-friendly interface, ThumbnailsPro is designed for YouTube success.

Artifactory is an AI-powered game asset generation tool that helps you create concepts for characters, icons, and backgrounds in seconds. With Artifactory, you can describe your task in text and generate images instantly. You can also use other images as references and train the model according to your style. Artifactory is easy to use and affordable, making it a great option for game developers of all levels.

SnapFusion.AI is an AI-powered photo editing tool that allows users to easily create custom AI avatars, professional headshots, social media pics, and more. Users can train their model with their own face and generate high-quality photos in just one click, without requiring any expertise in AI. The tool offers a user-friendly interface, diverse photo styles, high-quality image output, and flexible pricing plans to cater to various creative needs. SnapFusion prioritizes user privacy and data security, ensuring a safe and private editing experience.

EyePop.ai is a hassle-free AI vision partner designed for innovators to easily create and own custom AI-powered vision models tailored to their visual data needs. The platform simplifies building AI-powered vision models through a fast, intuitive, and fully guided process without the need for coding or technical expertise. Users can define their target, upload data, train their model, deploy and detect, and iterate and improve to ensure effective AI solutions. EyePop.ai offers pre-trained model library, self-service training platform, and future-ready solutions to help users innovate faster, offer unique solutions, and make real-time decisions effortlessly.

Tess is the first AI image generator that empowers artists to own their style by creating properly-licensed images. It offers a world-class image editor designed for AI, allowing users to generate art in a consistent visual style. Tess enables artists to create models, edit and customize their generations, and discover how AI can enhance their artistic style. With Tess, users can access copyright-safe generations created by real artists, ensuring ethical AI art practices.

AI Profile Pictures is a website that allows users to generate AI-generated profile pictures. Users can purchase credits to generate 200+ images, and then upload at least 10 photos of themselves (or their subject) for the AI model to train on. Once the photos are uploaded, users can wait 2-3 hours for the AI to generate their profile pictures. Users will have 7 days to generate additional photos if they are not satisfied with their results.

Genice is an online face swap tool that allows users to effortlessly swap faces in videos or images. With its advanced technology, Genice can generate realistic results by incorporating multiple face images, delivering superior quality compared to the method of using just a single face image. Users can train their custom model with just about 10 images and endlessly generate their dream photos or videos. Genice also offers a variety of features such as changing faces in any video or image effortlessly, generating images through style selection, and providing free credits to new sign-up users.

Unless is a conversational AI platform that helps organizations unlock their knowledge and provide better customer support. With Unless, you can train an AI model with your own knowledge base, documents, or website, and then let your customers or team engage in conversations with the AI through various channels. Unless is designed to be easy to use, even for non-technical staff, and it offers a variety of features to help you get the most out of your AI model.

AnythingYou.AI is an AI tool that generates beautiful profile pictures using AI avatars. Users can create custom AI avatars by uploading 10-20 selfies, and the tool will train a custom model for them immediately. The generated avatar images are high-quality and realistic, created using innovative technologies like Stable Diffusion and DreamBooth. Users can easily create avatars without the need for subscriptions or app installs, and get their avatar images in just 2 hours. The tool ensures user privacy by using images only for model training and deleting them immediately after avatar generation.

Facet is a cutting-edge generative imagery tool that helps creative professionals focus on what matters. It provides creative assistance without trading off artistic control. Facet helps overcome time and resource constraints that prevent trying out ideas. It offers an intuitive image generation experience with more than just text prompts, including image references, automatic prompt variations, and even custom models trained on the user's exact aesthetic. Facet allows users to train a custom model using their own images in minutes, generating endless assets in their exact vision. Users can add image references to any prompt, instantly getting images that adhere to their subject or style. Facet provides a collaborative canvas for users to riff with teammates and build off of each other's prompts and ideas.

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

llm-finetuning is a repository that provides a serverless twist to the popular axolotl fine-tuning library using Modal's serverless infrastructure. It allows users to quickly fine-tune any LLM model with state-of-the-art optimizations like Deepspeed ZeRO, LoRA adapters, Flash attention, and Gradient checkpointing. The repository simplifies the fine-tuning process by not exposing all CLI arguments, instead allowing users to specify options in a config file. It supports efficient training and scaling across multiple GPUs, making it suitable for production-ready fine-tuning jobs.

VLM-R1 is a stable and generalizable R1-style Large Vision-Language Model proposed for Referring Expression Comprehension (REC) task. It compares R1 and SFT approaches, showing R1 model's steady improvement on out-of-domain test data. The project includes setup instructions, training steps for GRPO and SFT models, support for user data loading, and evaluation process. Acknowledgements to various open-source projects and resources are mentioned. The project aims to provide a reliable and versatile solution for vision-language tasks.

ShapeLLM is the first 3D Multimodal Large Language Model designed for embodied interaction, exploring a universal 3D object understanding with 3D point clouds and languages. It supports single-view colored point cloud input and introduces a robust 3D QA benchmark, 3D MM-Vet, encompassing various variants. The model extends the powerful point encoder architecture, ReCon++, achieving state-of-the-art performance across a range of representation learning tasks. ShapeLLM can be used for tasks such as training, zero-shot understanding, visual grounding, few-shot learning, and zero-shot learning on 3D MM-Vet.

The KAN-GPT repository is a PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling. It provides a model for generating text based on prompts, with a focus on improving performance compared to traditional MLP-GPT models. The repository includes scripts for training the model, downloading datasets, and evaluating model performance. Development tasks include integrating with other libraries, testing, and documentation.

YuLan-Mini is a lightweight language model with 2.4 billion parameters that achieves performance comparable to industry-leading models despite being pre-trained on only 1.08T tokens. It excels in mathematics and code domains. The repository provides pre-training resources, including data pipeline, optimization methods, and annealing approaches. Users can pre-train their own language models, perform learning rate annealing, fine-tune the model, research training dynamics, and synthesize data. The team behind YuLan-Mini is AI Box at Renmin University of China. The code is released under the MIT License with future updates on model weights usage policies. Users are advised on potential safety concerns and ethical use of the model.

K2 (GeoLLaMA) is a large language model for geoscience, trained on geoscience literature and fine-tuned with knowledge-intensive instruction data. It outperforms baseline models on objective and subjective tasks. The repository provides K2 weights, core data of GeoSignal, GeoBench benchmark, and code for further pretraining and instruction tuning. The model is available on Hugging Face for use. The project aims to create larger and more powerful geoscience language models in the future.

Defog's SQLCoder is a family of state-of-the-art large language models (LLMs) designed for converting natural language questions into SQL queries. It outperforms popular open-source models like gpt-4 and gpt-4-turbo on SQL generation tasks. SQLCoder has been trained on more than 20,000 human-curated questions based on 10 different schemas, and the model weights are licensed under CC BY-SA 4.0. Users can interact with SQLCoder through the 'transformers' library and run queries using the 'sqlcoder launch' command in the terminal. The tool has been tested on NVIDIA GPUs with more than 16GB VRAM and Apple Silicon devices with some limitations. SQLCoder offers a demo on their website and supports quantized versions of the model for consumer GPUs with sufficient memory.

The fsdp_qlora repository provides a script for training Large Language Models (LLMs) with Quantized LoRA and Fully Sharded Data Parallelism (FSDP). It integrates FSDP+QLoRA into the Axolotl platform and offers installation instructions for dependencies like llama-recipes, fastcore, and PyTorch. Users can finetune Llama-2 70B on Dual 24GB GPUs using the provided command. The script supports various training options including full params fine-tuning, LoRA fine-tuning, custom LoRA fine-tuning, quantized LoRA fine-tuning, and more. It also discusses low memory loading, mixed precision training, and comparisons to existing trainers. The repository addresses limitations and provides examples for training with different configurations, including BnB QLoRA and HQQ QLoRA. Additionally, it offers SLURM training support and instructions for adding support for a new model.

LLM Foundry is a codebase for training, finetuning, evaluating, and deploying LLMs for inference with Composer and the MosaicML platform. It is designed to be easy-to-use, efficient _and_ flexible, enabling rapid experimentation with the latest techniques. You'll find in this repo: * `llmfoundry/` - source code for models, datasets, callbacks, utilities, etc. * `scripts/` - scripts to run LLM workloads * `data_prep/` - convert text data from original sources to StreamingDataset format * `train/` - train or finetune HuggingFace and MPT models from 125M - 70B parameters * `train/benchmarking` - profile training throughput and MFU * `inference/` - convert models to HuggingFace or ONNX format, and generate responses * `inference/benchmarking` - profile inference latency and throughput * `eval/` - evaluate LLMs on academic (or custom) in-context-learning tasks * `mcli/` - launch any of these workloads using MCLI and the MosaicML platform * `TUTORIAL.md` - a deeper dive into the repo, example workflows, and FAQs

AIMET is a library that provides advanced model quantization and compression techniques for trained neural network models. It provides features that have been proven to improve run-time performance of deep learning neural network models with lower compute and memory requirements and minimal impact to task accuracy. AIMET is designed to work with PyTorch, TensorFlow and ONNX models. We also host the AIMET Model Zoo - a collection of popular neural network models optimized for 8-bit inference. We also provide recipes for users to quantize floating point models using AIMET.

ProX is a lm-based data refinement framework that automates the process of cleaning and improving data used in pre-training large language models. It offers better performance, domain flexibility, efficiency, and cost-effectiveness compared to traditional methods. The framework has been shown to improve model performance by over 2% and boost accuracy by up to 20% in tasks like math. ProX is designed to refine data at scale without the need for manual adjustments, making it a valuable tool for data preprocessing in natural language processing tasks.

Cherry Data Selection project introduces a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, minimizing manual curation and cost for instruction tuning. The project focuses on selecting impactful training samples ('cherry data') to enhance LLM instruction tuning by estimating instruction-following difficulty. The method involves phases like 'Learning from Brief Experience', 'Evaluating Based on Experience', and 'Retraining from Self-Guided Experience' to improve LLM performance.

LLaMA Factory is a unified framework for fine-tuning 100+ large language models (LLMs) with various methods, including pre-training, supervised fine-tuning, reward modeling, PPO, DPO and ORPO. It features integrated algorithms like GaLore, BAdam, DoRA, LongLoRA, LLaMA Pro, LoRA+, LoftQ and Agent tuning, as well as practical tricks like FlashAttention-2, Unsloth, RoPE scaling, NEFTune and rsLoRA. LLaMA Factory provides experiment monitors like LlamaBoard, TensorBoard, Wandb, MLflow, etc., and supports faster inference with OpenAI-style API, Gradio UI and CLI with vLLM worker. Compared to ChatGLM's P-Tuning, LLaMA Factory's LoRA tuning offers up to 3.7 times faster training speed with a better Rouge score on the advertising text generation task. By leveraging 4-bit quantization technique, LLaMA Factory's QLoRA further improves the efficiency regarding the GPU memory.

DeRTa (Refuse Whenever You Feel Unsafe) is a tool designed to improve safety in Large Language Models (LLMs) by training them to refuse compliance at any response juncture. The tool incorporates methods such as MLE with Harmful Response Prefix and Reinforced Transition Optimization (RTO) to address refusal positional bias and strengthen the model's capability to transition from potential harm to safety refusal. DeRTa provides training data, model weights, and evaluation scripts for LLMs, enabling users to enhance safety in language generation tasks.

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