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Use this model Instructions to use sukritvemula/WebScrapeAgent-7B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started. May 1 15:25 Add TurboQuant 3-bit + HQQ mixed-precision compression pipeline (sections 9-11) 15:08 Rewrite from scratch — exact copy of official unsloth Qwen2.5-7B notebook pattern with pinned deps 14:49 Speed fix v3: seq 1024, bs 4, max_steps=800, max_length param, LoRA r=16 — target ~2h on T4 14:19 Speed fix: packing=True, seq 2048, bs 2, 1 epoch — estimated ~2h on T4 instead of 177h 14:10 Fix: train_on_responses_only needs explicit Qwen2.5 ChatML parts + warmup_ratio→warmup_steps + total_mem→total_memory 12:59 Upload generate_v2_data.py with huggingface_hub 12:59 Upload WebScrapeAgent_Training_v2.ipynb with huggingface_hub 03:57 Upload WebScrapeAgent_Training.ipynb with huggingface_hub 03:57 Upload evaluate.py with huggingface_hub 03:57 Upload webscrape_agent.py with huggingface_hub 03:57 Upload train.py with huggingface_hub 03:57 Upload README.md with huggingface_hub 03:55 initial commit