LLM Models

We opensource our Aquila2 series, now including Aquila2 , the base language models, namely Aquila2-7B and Aquila2-34B , as well as AquilaChat2 , the chat models, namely AquilaChat2-7B and AquilaChat2-34B , as well as the long-text chat models, namely AquilaChat2-7B-16k and Aquila…

We introduce DeepSeek-Prover-V2, an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by DeepSeek-V3. The cold-start training procedure begins by prompting DeepSe…

A small ~110M parameter language model implementing the DeepSeek-V4 architecture from scratch. This is the pretrained base model — see HuggingFaceTB/nanowhale-100m for the SFT/chat version.

DeepSeek-V2.5-1210 is an upgraded version of DeepSeek-V2.5, with improvements across various capabilities:

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SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification

Llama-2-7B-32K-Instruct is an open-source, long-context chat model finetuned from Llama-2-7B-32K, over high-quality instruction and chat data. We built Llama-2-7B-32K-Instruct with less than 200 lines of Python script using Together API, and we also make the recipe fully availabl…

Qwen3-Swallow v0.2 is a family of large language models available in 8B , 30B-A3B , and 32B parameter sizes. Built as bilingual Japanese-English models, they were developed through Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), and Reinforcement Learning with Verifia…

DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning

0. TL;DR 1. Model Details 2. Training Details 3. Usage 4. Evaluation 5. Citation

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Llama 3.1 Swallow is a series of large language models (8B, 70B) that were built by continual pre-training on the Meta Llama 3.1 models. Llama 3.1 Swallow enhanced the Japanese language capabilities of the original Llama 3.1 while retaining the English language capabilities. We u…