| huggingface/transformers |
119,240 |
|
64 |
2,484 |
about 2 years ago |
125 |
November 15, 2023 |
946 |
apache-2.0 |
Python |
| 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. |
| xtekky/gpt4free |
52,083 |
|
0 |
10 |
about 2 years ago |
83 |
December 06, 2023 |
106 |
gpl-3.0 |
Python |
| The official gpt4free repository | various collection of powerful language models |
| dair-ai/Prompt-Engineering-Guide |
40,069 |
|
0 |
0 |
about 2 years ago |
0 |
|
49 |
mit |
MDX |
| 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering |
| LAION-AI/Open-Assistant |
36,197 |
|
0 |
0 |
about 2 years ago |
0 |
|
284 |
apache-2.0 |
Python |
| OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so. |
| tatsu-lab/stanford_alpaca |
24,846 |
|
0 |
0 |
almost 3 years ago |
0 |
|
160 |
apache-2.0 |
Python |
| Code and documentation to train Stanford's Alpaca models, and generate the data. |
| microsoft/generative-ai-for-beginners |
23,219 |
|
0 |
0 |
about 2 years ago |
0 |
|
26 |
mit |
Jupyter Notebook |
| 12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/ |
| arc53/DocsGPT |
17,677 |
|
0 |
0 |
3 months ago |
11 |
September 13, 2023 |
110 |
mit |
Python |
| Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents. |
| microsoft/unilm |
16,971 |
|
0 |
0 |
about 2 years ago |
0 |
|
517 |
mit |
Python |
| Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities |
| mlc-ai/mlc-llm |
15,290 |
|
0 |
0 |
about 2 years ago |
0 |
|
197 |
apache-2.0 |
Python |
| Enable everyone to develop, optimize and deploy AI models natively on everyone's devices. |
| deepset-ai/haystack |
12,474 |
|
0 |
30 |
about 2 years ago |
100 |
November 09, 2023 |
346 |
apache-2.0 |
Python |
| :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots. |
