---
license: mit
library_name: peft
base_model: NousResearch/Llama-2-7b-hf
datasets:
- Bton/vine-reviews
tags:
- peft
- lora
- text-generation
- personalized
- fine-tuned
- amazon-reviews
- jsonl
pipeline_tag: text-generation
---
# ⚠️ Warning: Occasionally starts speaking German for no reason. dunno.
Trained on a Google Colab T4 GPU — not the prettiest, but it gets the job done.
---
# 🧠 Fine-Tuned LLaMA 2 (7B) with PEFT
## Model Summary
This model is a parameter-efficient fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf), built using the `peft` library with LoRA.
It was trained to replicate the tone, language, and reviewing habits of my dad, a long-time Amazon Vine reviewer.
Training was done on a custom dataset derived from years of Amazon reviews, scraped and structured into instruction-tuned format for use in conversational modeling.
Example format:
```json
{"text": "[INST] Does not include rechargeable batteries [/INST] I thought that these included rechargeable batteries, but after re-reading the description... "}
The data was split into:
train.jsonl
valid.jsonl
test.jsonl
Each entry follows the [INST] instruction [/INST] response structure to support compatibility with LLaMA-style dialogue tuning.
✅ Intended Use
Direct Use
Regenerate product reviews in the style of a prolific Amazon Vine reviewer
Emulate personal tone in ecommerce content, chatbots, or stylized summaries
Out-of-Scope Use
Not for high-stakes domains (legal, medical, financial)
Not intended for impersonation, misinformation, or deceptive representations
⚠️ Risks and Limitations
May reflect strong personal opinions — especially about polyester and glove insulation
Not guaranteed to be factually accurate or hallucination-free
Prone to occasional repetition
Can randomly switch to German mid-sentence (don’t ask, we don’t know either)
🏋️ Training Details
PEFT Method: LoRA (Low-Rank Adaptation)
Precision: bf16
Training Data: Bton/vine-reviews — scraped, cleaned, and formatted Amazon Vine reviews written by better reviewer than myself.
Data Format: JSONL with instruction-style [INST] ... [/INST] ... prompts
Hardware: Google Colab 1 x T4 GPU