Documented Gensyn base
Hub tags and the model card both identify Gensyn/Qwen2.5-0.5B-Instruct as the base model and fine-tune source.
Open Source Model Profile · Karai031
This Karai031 model is a 494M-parameter Qwen2 text-generation fine-tune. Its model card identifies Gensyn/Qwen2.5-0.5B-Instruct as the base with TRL and GRPO training.
The model is published by Karai031 as a text-generation fine-tune of Gensyn/Qwen2.5-0.5B-Instruct. The captured configuration identifies Qwen2ForCausalLM with a qwen2 model type, and Safetensors metadata reports 494,032,768 parameters. According to the model card, it was trained using TRL, with GRPO named as the training procedure.
Hub tags and the model card both identify Gensyn/Qwen2.5-0.5B-Instruct as the base model and fine-tune source.
According to the model card, training used TRL with GRPO, the method introduced in DeepSeekMath work.
Captured config identifies Qwen2ForCausalLM and qwen2, with Safetensors metadata reporting 494,032,768 parameters.
The model card documents a transformers text-generation pipeline snippet for running the model.
Source: Karai031/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-hardy_stubby_hawk
Captured: Unknown. Processed: 2026-09-07T19:35:08.683864+00:00.
Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-hardy_stubby_hawk This model is a fine-tuned version of Gensyn/Qwen2.5-0.5B-Instruct . It has been trained using TRL . Quick start from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline( "text-generation" , model= "Karai031/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-hardy_stubby_hawk" , device= "cuda" ) output = generator([{ "role" : "user" , "content" : question}], max_new_tokens= 128 , return_full_text= False )[ 0 ] print (output[ "generated_text" ]) Tr…
F001F002F003F004F005F006F007F008F009F010F011F012F013