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Retail & Inventory Communication Fine-Tuning Dataset

Stock notifications, reorder requests, and supplier coordination.

Fine-tune a model on this dataset

$29 for the dataset. Training is priced separately by model, starting at $47.

What is in this dataset

708 instruction-response pairs covering stock notifications, reorder requests, and supplier coordination. Each pair is a realistic question with a full written answer, in the JSONL format used for supervised fine-tuning. No synthetic filler, no duplicated rows.

Example pairs

Real rows from the dataset, shown in full.

Draft a reorder request to our supplier, EcoPack Solutions, for 200 units of biodegradable sandwich bags (SKU: BSB-2024), referencing our contract rate of $0.12 per unit and requesting delivery within 10 business days.

Subject: Reorder Request – Biodegradable Sandwich Bags (SKU: BSB-2024) Dear EcoPack Solutions Team, We are submitting a reorder request for 200 units of biodegradable sandwich bags (SKU: BSB-2024) at the agreed contract rate of $0.12 per unit, totaling $24.00. Please process this order for delivery within 10 business days from receipt of this request. Confirm availability and ship date by replying to this email. If there are any pricing or stock discrepancies, please notify us immediately. Thank you, [Your Name] Retail Operations Manager

Write a back-in-stock notification email to a customer named Sarah who requested an alert for the 'Midnight Blue' ceramic mug (SKU: MUG-045). Mention the price is $14.99 and include a direct link to purchase.

Subject: Great News! Midnight Blue Mug (SKU: MUG-045) Is Back in Stock Hi Sarah, You asked us to let you know when the Midnight Blue ceramic mug (SKU: MUG-045) was available again. Good news—it’s now back in stock at $14.99! Grab yours before they sell out again: [Insert direct purchase link here] If you have any questions or need help with your order, just reply to this email. Happy sipping, The [Store Name] Team

Draft an apology email to a customer, James, who ordered a 'Sahara' hiking backpack (SKU: HP-302) that is now out of stock. Explain the delay is due to a supplier issue and offer a 10% discount on his next purchase.

Subject: Apology for Out-of-Stock Issue – Sahara Hiking Backpack (SKU: HP-302) Dear James, We sincerely apologize for the inconvenience regarding your order for the Sahara hiking backpack (SKU: HP-302). Unfortunately, this item is currently out of stock due to an unforeseen delay from our supplier. We understand how disappointing this must be, especially after you placed your order. As a gesture of our apology, we’d like to offer you a 10% discount on your next purchase with us. Use code SORRY10 at checkout, valid for 30 days. We are working to restock the Sahara backpack as soon as possible. If you’d like, we can notify you when it’s available, or you can reply to this email to discuss…

Who this is for

Shops and suppliers coordinating stock, reorders, and back-in-stock notices.

Which models this works with

The dataset is plain JSONL, so it works with any instruction-tuned open model. On Rebiha you can train it directly on:

Training uses LoRA, or QLoRA on a 4-bit base for larger models. Your base model's weights are never modified — training produces a separate adapter.

How it works

  1. Pick this dataset and a base model.
  2. Rebiha runs the job on a managed GPU. You set up nothing.
  3. Download your model: a ready-to-run GGUF, plus developer assets (adapter, tokenizer, configs).

Fine-tuning or RAG?

Use RAG when the model needs facts that change — your prices, your documents, today's inventory. Use fine-tuning when you want consistent style and structure without prompting for it every time. This dataset teaches the shape of a good answer in this domain, not facts to look up.

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