Customer Support LoRA Adapter (Llama-3.2-3B-Instruct · MLX)
This repository provides LoRA adapters fine-tuned on the
Bitext Customer Support dataset.
The goal is placeholder-safe answers (e.g., {{Order Number}}
, {{Website URL}}
must remain unchanged).
- Base model:
meta-llama/Llama-3.2-3B-Instruct
- Runtime: Apple Silicon MLX
- This repo contains:
adapters.safetensors
(LoRA only; no base weights)
You must accept/download the base model under its own license (Meta Llama 3.2 Community License).
This repo does not include base weights.
Quickstart (MLX CLI)
Install once:
pip install -U mlx-lm
Generate with adapter:
python -m mlx_lm.generate \
--model meta-llama/Llama-3.2-3B-Instruct \
--adapter-path batuhne/customer-support-llm \
--prompt "Hello, please cancel order {{Order Number}}" \
--max-tokens 128 --temp 0.2
Interactive chat (optional):
python -m mlx_lm.chat \
--model meta-llama/Llama-3.2-3B-Instruct \
--adapter-path batuhne/customer-support-llm
Recommended system prompt
Keep placeholders exactly:
You are a concise, helpful customer support agent. Preserve placeholders exactly as given (e.g., {{Order Number}}, {{Website URL}}).
Notes
Trained for placeholder integrity; do not modify {{…}} tokens in outputs.
Use MLX quantized base weights if you need lower RAM/VRAM usage on Apple Silicon.
Limitations
Adapter quality is tied to the base model and dataset scope (customer support).
This is not a general safety or policy layer; review outputs before production use.
License
Base model license: Meta Llama 3.2 Community License (must be accepted separately).
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Model tree for batuhne/customer-support-llm
Base model
meta-llama/Llama-3.2-3B-Instruct