Qwen2 0.5B Gensyn fine-tune
Captured configuration records Qwen2ForCausalLM with about 0.49B parameters, and the model card describes a fine-tune of Gensyn/Qwen2.5-0.5B-Instruct.
Open Source Model Profile · Gigimelon
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-cunning_stalking_fly is a 0.49B-parameter Qwen2 fine-tune from Gigimelon. The model card lists Gensyn/Qwen2.5-0.5B-Instruct with TRL and GRPO.
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-cunning_stalking_fly is published by Gigimelon as a Qwen2 text-generation model. The captured configuration identifies Qwen2ForCausalLM with model type qwen2, and Safetensors metadata reports 494,032,768 parameters. According to the model card, it fine-tunes Gensyn/Qwen2.5-0.5B-Instruct.
Captured configuration records Qwen2ForCausalLM with about 0.49B parameters, and the model card describes a fine-tune of Gensyn/Qwen2.5-0.5B-Instruct.
Hub tags record rl-swarm, grpo, and trl, and the model card states training with TRL and GRPO linked to the DeepSeekMath method.
According to the model card, generation uses the Transformers text-generation pipeline with a user-role input and 128 max new tokens in the example.
Source: Gigimelon/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-cunning_stalking_fly
Captured: Unknown. Processed: 2026-09-07T19:35:05.569260+00:00.
Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-cunning_stalking_fly 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= "Gigimelon/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-cunning_stalking_fly" , device= "cuda" ) output = generator([{ "role" : "user" , "content" : question}], max_new_tokens= 128 , return_full_text= False )[ 0 ] print (output[ "generated_text…
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