LLM Models
Browse the world's large language models. Compare parameters, benchmarks, VRAM and more.
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggi…
[\[📂 GitHub\]](https://github.com/OpenGVLab/InternVL) [\[📜 InternVL 1.0\]](https://huggingface.co/papers/2312.14238) [\[📜 InternVL 1.5\]](https://huggingface.co/papers/2404.16821) [\[📜 InternVL 2.5\]](https://huggingface.co/papers/2412.05271) [\[📜 InternVL2.5-MPO\]](https://huggi…
We identified and fixed an issue related to a wrong permutation of some projections, which affects generation quality. To use the new model revision, please load as follows:
Introducing Kimi-Dev: A Strong and Open-source Coding LLM for Issue Resolution Kimi-Dev Team
🤗 Hugging Face • 🤖 ModelScope • 🟣 wisemodel
🤗 Hugging Face 🖥️ Official Website 🕖 HunyuanAPI 🕹️ Demo 🤖 ModelScope
MiniCPM 技术报告 Technical Report OmniLMM 多模态模型 Multi-modal Model CPM-C 千亿模型试用 ~100B Model Trial
Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, Mohammad Rastegari
0. TL;DR 1. Model Details 2. Training Details 3. Usage 4. Evaluation 5. Citation
Large Action Models (LAMs) are advanced language models designed to enhance decision-making by translating user intentions into executable actions. As the brains of AI agents , LAMs autonomously plan and execute tasks to achieve specific goals, making them invaluable for automati…
Our Swallow model has undergone continual pre-training from the Llama 2 family, primarily with the addition of Japanese language data. The tuned versions use supervised fine-tuning (SFT). Links to other models can be found in the index.
Based on LFM2-1.2B, LFM2-1.2B-Extract is designed to extract important information from a wide variety of unstructured documents (such as articles, transcripts, or reports) into structured outputs like JSON, XML, or YAML.