Qwen2.5-0.5B-Instruct-Gensyn-Swarm-aquatic_stubby_chicken

Model overview

The model is published by 0xnoob 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.

Recorded capabilities

Use cases in the source record

• Conversational text generation through the model card's documented transformers pipeline workflow.
• RL-swarm and GRPO fine-tune research building on the documented Gensyn Qwen2.5-0.5B-Instruct base.

Limitations and unknowns

• No evaluation results were extracted from this record.
• No license value was extracted from this record.
• No context-window value, hardware requirement, or dataset detail was extracted.
• Provider state is historical snapshot data, not independently refreshed current availability.
• Base-model and training details come from a brief publisher model card and were not independently verified by Ethen.

Source and provenance

Source: 0xnoob/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-aquatic_stubby_chicken

Captured: Unknown. Processed: 2026-09-07T19:35:01.837779+00:00.

Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-aquatic_stubby_chicken 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= "0xnoob/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-aquatic_stubby_chicken" , device= "cuda" ) output = generator([{ "role" : "user" , "content" : question}], max_new_tokens= 128 , return_full_text= False )[ 0 ] print (output[ "generated_tex…