The Wolfram LLM Benchmarking Project tracks model performance on a code-generation task written in Wolfram Language.
Awesome ML
This repository collects machine learning resources, including language models, tools, interfaces, and retrieval systems.

About Awesome ML
Awesome ML is a repository that collects links to machine learning resources focused on LLM, analytics and datascience topics. It organizes entries into sections such as tools, native and web interfaces, backends, retrieval systems, datasets, benchmarking, and image, video and audio models.
Content is split across topic files including llm-tools, image-generation, video-ai, audio-ai and marketing-data-science, and contributions are accepted through pull requests.
Key features
- Lists of open LLM models and related tools
- Native GUIs, web GUIs and backends for models
- Retrieval Augmented Generation and agent resources
- Code generation and prompt templating references
- Image, video and audio model sections including music generation
- Fine tuning, training, merging and quantization material
- Open source repository under MIT license
- Accepts contributions through pull requests
- Separate files for audio, image, video and marketing data science topics
Awesome ML at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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