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

Model overview

The model is published by 0xBahar as a text-generation fine-tune. The captured configuration identifies Qwen2ForCausalLM with model type qwen2, and Safetensors metadata reports 494,032,768 parameters. According to the model card, it is a fine-tuned version of Gensyn/Qwen2.5-0.5B-Instruct and was trained using TRL.

Recorded capabilities

Use cases in the source record

• Conversational text-generation work using the Transformers pipeline workflow documented in the model card.
• GRPO and RL-swarm fine-tune reuse where the recorded Gensyn lineage and TRL workflow are relevant.

Limitations and unknowns

• No license value was extracted from this record.
• No evaluation results, context-window value, or hardware requirements were extracted.
• Training detail beyond TRL and GRPO method naming was not extracted.
• Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: 0xBahar/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-bold_aquatic_cod

Captured: Unknown. Processed: 2026-09-07T19:35:01.693432+00:00.

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