InternVL3-8B (LoRA) finetuned on shopping logs
This repository contains LoRA adapters for OpenGVLab/InternVL3-8B finetuned on
custom shopping assistant logs.
Training
- Technique: LoRA (r=128, alpha=256, dropout=0.05)
- Target modules: qkv, proj, fc1, fc2
- Precision: bf16
Usage
1from transformers import AutoModelForCausalLM, AutoTokenizer
2from peft import PeftModel
3from PIL import Image
4import torch
5
6base_id = "OpenGVLab/InternVL3-8B"
7lora_id = "harsheet35/internvl3-8b-shopping-lora"
8
9model = AutoModelForCausalLM.from_pretrained(
10 base_id, torch_dtype=torch.bfloat16, trust_remote_code=True
11)
12tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)
13
14model = PeftModel.from_pretrained(model, lora_id)
15model.img_context_token_id = tokenizer.convert_tokens_to_ids("<IMG_CONTEXT>")
16
17# Inference example
18image = Image.open("product.jpg").convert("RGB")
19response = model.chat(
20 tokenizer=tokenizer,
21 pixel_values=image,
22 question="Describe the product in the image.",
23 generation_config={"max_new_tokens": 256, "temperature": 0.7}
24)
25print(response)
base_model: ./downloaded_models/internvl3-8b
library_name: peft
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