Qwen2.5-7B-Instruct-SFT

Model overview

Qwen2.5-7B-Instruct-SFT is published by od2961 as a Qwen2 text-generation model. The captured configuration identifies Qwen2ForCausalLM, and Safetensors metadata reports 7,615,616,512 parameters. According to the model card, it is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct trained using TRL.

Recorded capabilities

Use cases in the source record

• Conversational text-generation experiments using the captured Qwen2 configuration and Transformers pipeline support.
• SFT and TRL workflow experiments building on the publisher-documented fine-tune of Qwen2.5-7B-Instruct.

Limitations and unknowns

• No license value was extracted from this record.
• No evaluation results, context-window value, dataset, or hardware detail were extracted.
• Provider state is historical snapshot data and should be refreshed before being presented as current.
• Base-model and training details come from a brief publisher model card and were not independently verified by Ethen.

Source and provenance

Source: od2961/Qwen2.5-7B-Instruct-SFT

Captured: Unknown. Processed: 2026-09-07T19:35:27.542942+00:00.

Model Card for Qwen2.5-7B-Instruct-SFT This model is a fine-tuned version of Qwen/Qwen2.5-7B-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= "od2961/Qwen2.5-7B-Instruct-SFT" , device= "cuda" ) output = generator([{ "role" : "user" , "content" : question}], max_new_tokens= 128 , return_full_text= False )[ 0 ] print (output[ "generated_text" ]) Training procedure This model was trained with SFT. Framework vers…