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dongbobo/
adapter-checkpoint-lora

Name: adapter-checkpoint-lora
Availability: InStock

meta-llama/Llama-2-7b-hf

adapter

apache-2.0

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Adapter Checkpoint — LoRA (Llama-2-7b)

This repository contains a LoRA adapter checkpoint trained on top of meta-llama/Llama-2-7b-hf for chat / instruction-following tasks.

Repository Contents

Path	Description
`adapter_config.json`	PEFT / LoRA configuration (rank, alpha, target modules …)
`adapter_model.bin`	Serialised adapter weights
`examples/chat/zero_shot/prompt.json`	Zero-shot chat prompt template
`examples/chat/few_shot/prompt.json`	Few-shot chat prompt template

Quick Start

python

from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "dongbobo/adapter-checkpoint-lora"

config    = PeftConfig.from_pretrained(repo_id)
tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
base      = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path)
model     = PeftModel.from_pretrained(base, repo_id)
model.eval()

inputs = tokenizer("Hello, how are you?", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Prompt Templates

Two ready-to-use prompt templates are provided for chat inference.

Zero-Shot Template

No in-context examples — the model relies purely on its instruction tuning.

👉 examples/chat/zero_shot/prompt.json

json

{
  "template": {
    "system": "You are a helpful, respectful, and honest assistant ...",
    "user": "{{user_message}}",
    "assistant": ""
  }
}

Few-Shot Template

Three canonical Q&A demonstrations are prepended to steer the model's style.

👉 examples/chat/few_shot/prompt.json

json

{
  "template": {
    "system": "You are a helpful, respectful, and honest assistant ...",
    "shots": ["..."],
    "user": "{{user_message}}",
    "assistant": ""
  }
}

Adapter Configuration

Key hyperparameters (see adapter_config.json for the full schema):

Parameter	Value
`peft_type`	`LORA`
`task_type`	`CAUSAL_LM`
`r`	8
`lora_alpha`	16
`lora_dropout`	0.05
`target_modules`	`q_proj`, `v_proj`
`bias`	`none`

License

Released under the Apache 2.0 licence.