Model: ubitech-edg/qwen2.5-72b-cpt-sft
Author: ubitech-edg
Pipeline: text-generation
Library: transformers
Tags: transformers, safetensors, qwen2, text-generation, causal-lm, two-stage-training, continual-pretraining, supervised-fine-tuning, synthetic-qa, lora, axolotl, deepspeed, qwen, llava, eu-hpc, conversational, en, dataset:arxiv, dataset:gov, dataset:news, dataset:wikipedia, dataset:axolotl_deduplicated_synthetic_qa, base_model:ubitech-edg/qwen2.5-72b-cpt, base_model:adapter:ubitech-edg/qwen2.5-72b-cpt, license:apache-2.0, text-generation-inference, endpoints_compatible, 4-bit, bitsandbytes, region:us
Base models (adapter): id: ubitech-edg/qwen2.5-72b-cpt
Card metadata: language: en
license: apache-2.0
tags: text-generation, causal-lm, two-stage-training, continual-pretraining, supervised-fine-tuning, synthetic-qa, lora, axolotl, deepspeed, transformers, qwen, llava, eu-hpc
datasets: arxiv, gov, news, wikipedia, axolotl_deduplicated_synthetic_qa
metrics: loss
library_name: transformers
framework: pytorch
base_model: ubitech-edg/qwen2.5-72b-cpt
model_name: qwen2.5-72b-cpt-sft
pipeline_tag: text-generation
task_categories: text-generation, question-answering
model_type: AutoModelForCausalLM
inference: parameters: max_new_tokens: 512
temperature: 0.7
top_p: 0.9
trained_on: Leonardo EuroHPC
description: Two-stage training (CPT + SFT) of Qwen2.5-72B using Axolotl and DeepSpeed ZeRO-1. The model was trained with 4-bit NF4 LoRA adapters: first on text corpora for continual pretraining, then on deduplicated synthetic QA pairs for supervised fine-tuning to enhance question-answering, reasoning, and response generation capabilities. This repository hosts LoRA adapters for the SFT stage only, designed to be loaded on top of ubitech-edg/qwen2.5-72b-cpt (which itself loads on Qwen/Qwen2.5-72B).
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Created: 2025-10-31 20:39:39