LLM Models

Developed by : Upstage Backbone Model : LLaMA Variations : It has different model parameter sizes and sequence lengths: 30B/1024, 30B/2048, 65B/1024 Language(s) : English Library : HuggingFace Transformers License : This model is under a Non-commercial Bespoke License and governe…

Emu3: Next-Token Prediction is All You Need

StableLM-Tuned-Alpha is a suite of 3B and 7B parameter decoder-only language models built on top of the StableLM-Base-Alpha models and further fine-tuned on various chat and instruction-following datasets.

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ MiMo-VL Technical Report ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Nous-Yarn-Mistral-7b-128k is a state-of-the-art language model for long context, further pretrained on long context data for 1500 steps using the YaRN extension method. It is an extension of Mistral-7B-v0.1 and supports a 128k token context window.

Gemma-2-Llama-Swallow series was built by continual pre-training on the gemma-2 models. Gemma 2 Swallow enhanced the Japanese language capabilities of the original Gemma 2 while retaining the English language capabilities. We use approximately 200 billion tokens that were sampled…

🐙 GitHub • 👾 Discord • 🐤 Twitter • 💬 WeChat 📝 Paper • 💪 Tech Blog • 🙌 FAQ • 📗 Learning Hub

CodeT5 is a family of encoder-decoder language models for code from the paper: CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation by Yue Wang, Weishi Wang, Shafiq Joty, and Steven C.H. Hoi.

sbintuitions/sarashina2.2-1b-instruct-v0.1

GPT-OSS-Swallow v0.1 is a family of large language models available in 20B and 120B parameter sizes. Built as bilingual Japanese-English models, they were developed through Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), and Reinforcement Learning with Verifiable Rewa…

Gemma-2-Llama-Swallow series was built by continual pre-training on the gemma-2 models. Gemma 2 Swallow enhanced the Japanese language capabilities of the original Gemma 2 while retaining the English language capabilities. We use approximately 200 billion tokens that were sampled…

InstructBLIP model using Vicuna-13b as language model. InstructBLIP was introduced in the paper InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning by Dai et al.