# Scientific Q&A

OpenThinker3-7B-GGUF is a quantized version of open-thoughts/OpenThinker3-7B, optimized for efficient inference. It is fine-tuned based on Qwen/Qwen2.5-7B-Instruct and performs excellently on mathematical, code, and scientific problems.

Falcon-H1 is an efficient hybrid architecture language model developed by TII, combining the strengths of Transformers and Mamba architectures, supporting English and multilingual tasks.

Falcon-H1 is a causal decoder-only language model developed by TII with a hybrid Transformers+Mamba architecture, supporting English and multilingual tasks.

YuLan-Mini-Instruct is a compact yet powerful 2.4-billion-parameter text generation model, specializing in mathematical and code reasoning tasks with support for both English and Chinese.

Einstein-v4-7B is a large language model fully fine-tuned on diverse scientific datasets based on Mistral-7B-v0.1, specializing in STEM field tasks

FLAN-T5 is an instruction-fine-tuned language model based on T5, achieving superior performance through fine-tuning on over 1,000 multilingual tasks with the same parameter count