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Rohit-Katkar2003/qwen2-vl-8b-lora-finetune
qwen2-vl-8b-lora-finetune is a machine learning model from Rohit-Katkar2003. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This repository contains LoRA adapters only.
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Updated Dec 29, 2025
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From the Hugging Face model README
This repository contains LoRA adapters only.
Base model:
## load the model from my own huggingface
from unsloth import FastVisionModel
model, tokenizer = FastVisionModel.from_pretrained(
"Rohit-Katkar2003/qwen2-vl-8b-lora-finetune",
load_in_4bit=True
)
FastVisionModel.for_inference(model) # Enable for inference!
question = "what are the components in diagram give me response in markdown format with all the connection and components?"
url = "https://instrumentationtools.com/wp-content/uploads/2016/09/instrumentationtools.com_piping-and-instrumentation-diagram.jpg"
res = requests.get(url)
image = Image.open(BytesIO(res.content))
messages = [
{"role": "user", "content": [
{"type": "image"},
{"type": "text", "text": question}
]}
]
input_text = tokenizer.apply_chat_template(messages, add_generation_prompt = True)
inputs = tokenizer(
image,
input_text,
add_special_tokens = False,
return_tensors = "pt",
).to("cuda")
from transformers import TextStreamer
text_streamer = TextStreamer(tokenizer, skip_prompt = True)
_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 1024,
use_cache = True, temperature = 0.3, min_p = 0.1)
This qwen3_vl model was trained 2x faster with Unsloth