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

Model overview

Qwen2.5-0.5B-Instruct-Gensyn-Swarm-lightfooted_sprightly_finch is published by Saifbox as a Qwen2 text-generation model. The captured configuration identifies Qwen2ForCausalLM 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 trained with GRPO using TRL.

Recorded capabilities

Use cases in the source record

• Conversational text-generation experiments on the documented Gensyn Qwen2.5-0.5B-Instruct lineage.
• Small-model GRPO and TRL workflow study using the documented Transformers pipeline example.

Limitations and unknowns

• No evaluation results were extracted from this record.
• No context-window value was extracted.
• No license value was captured, so reuse terms are unknown from this record.
• No detailed training hyperparameters or dataset were extracted beyond GRPO, TRL, and the pipeline example.
• Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: Saifbox/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-lightfooted_sprightly_finch

Captured: Unknown. Processed: 2026-09-07T19:35:15.357351+00:00.

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