Qwen2.5-0.5B-Instruct finetune
According to the model card, the model is a fine-tuned version of unsloth/Qwen2.5-0.5B-Instruct, matching the hub base-model tags.
Open Source Model Profile · Gelsinger
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-energetic_placid_chinchilla
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-energetic_placid_chinchilla is a 0.49B-parameter Qwen2 finetune of unsloth/Qwen2.5-0.5B-Instruct with TRL and GRPO notes.
- Publisher
- Gelsinger
- Task
- text-generation
- Model type
- qwen2
- License
- Unknown
- Library
- transformers
- Publication status
- Accepted · not indexed
Model overview
Qwen2.5-0.5B-Instruct-Gensyn-Swarm-energetic_placid_chinchilla is published by Gelsinger 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 finetunes unsloth/Qwen2.5-0.5B-Instruct with TRL and GRPO.
Recorded capabilities
TRL and GRPO training notes
According to the model card, training used TRL with GRPO, and hub tags include rl-swarm, grpo, gensyn, and trl.
Transformers pipeline example
According to the model card, the publisher shows Transformers pipeline text generation with a user-role question and 128 max new tokens.
Use cases in the source record
- Small-model chat-style text generation using the publisher's documented Transformers pipeline setup.
- RL-swarm and GRPO finetuning comparisons built around the documented unsloth/Qwen2.5-0.5B-Instruct lineage.
Limitations and unknowns
- No license value was extracted from this record.
- No evaluation results, context-window value, dataset details, or hardware figures were extracted.
- Provider state is historical snapshot data and should be refreshed before being presented as current.
Source and provenance
Source: Gelsinger/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-energetic_placid_chinchilla
Captured: Unknown. Processed: 2026-09-07T19:35:05.561621+00:00.
Model Card for Qwen2.5-0.5B-Instruct-Gensyn-Swarm-energetic_placid_chinchilla This model is a fine-tuned version of unsloth/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= "Gelsinger/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-energetic_placid_chinchilla" , device= "cuda" ) output = generator([{ "role" : "user" , "content" : question}], max_new_tokens= 128 , return_full_text= False )[ 0 ] print (output[…
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