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

Model overview

Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf is published by Dassem as a Transformers text-generation fine-tune. The captured configuration identifies Qwen2ForCausalLM with model type qwen2 and about 0.49B Safetensors parameters. According to the model card, it fine-tunes Gensyn/Qwen2.5-0.5B-Instruct using TRL with a GRPO training procedure.

Recorded capabilities

Use cases in the source record

• Conversational text-generation workflows using the documented Transformers pipeline example.
• Small-model RL-swarm and GRPO experiments building on the tagged Gensyn base.

Limitations and unknowns

• No evaluation results were extracted from this record.
• No license value was extracted for this record.
• No context-window value was extracted from this record.
• Training detail is limited to the publisher's TRL and GRPO notes; dataset, steps, and compute were not extracted.
• Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: Dassem/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf

Captured: Unknown. Processed: 2026-09-07T19:35:04.456453+00:00.

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