Update README.md

README.md

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----
-license: mit
-language:
-- multilingual
-pipeline_tag: image-text-to-text
-tags:
-- nlp
-- vision
-- internvl
-base_model:
-- OpenGVLab/InternVL2-1B
-base_model_relation: quantized
----
-
-# InternVL2-1B-int8-ov
-
- * Model creator: [OpenGVLab](https://huggingface.co/OpenGVLab)
- * Original model: [InternVL2-1B](https://huggingface.co/OpenGVLab/InternVL2-1B)
-
-## Description
-
-This is [OpenGVLab/InternVL2-1B](https://huggingface.co/OpenGVLab/InternVL2-1B) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2024/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
-
-
-## Quantization Parameters
-
-Weight compression was performed using `nncf.compress_weights` with the following parameters:
-* mode: **INT8_ASYM**
-
-## Compatibility
-
-The provided OpenVINO™ IR model is compatible with:
-
-* OpenVINO version 2025.0.0 and higher
-* Optimum Intel 1.21.0 and higher
-
-## Running Model Inference with [Optimum Intel](https://huggingface.co/docs/optimum/intel/index)
-
-1. Install packages required for using [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) integration with the OpenVINO backend:
-
-```
-pip install --pre -U --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/pre-release openvino_tokenizers openvino
-
-pip install git+https://github.com/huggingface/optimum-intel.git
-```
-
-2. Run model inference
-
-```
-from PIL import Image 
-import requests 
-from optimum.intel.openvino import OVModelForVisualCausalLM
-from transformers import AutoTokenizer, TextStreamer
-
-model_id = "OpenVINO/InternVL2-1B-int8-ov"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
-
-ov_model = OVModelForVisualCausalLM.from_pretrained(model_id, trust_remote_code=True)
-prompt = "What is unusual on this picture?"
-
-url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
-image = Image.open(requests.get(url, stream=True).raw)
-
-inputs = ov_model.preprocess_inputs(text=prompt, image=image, tokenizer=tokenizer, config=ov_model.config)
-
-generation_args = { 
-    "max_new_tokens": 100, 
-    "streamer": TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
-} 
-
-generate_ids = ov_model.generate(**inputs, **generation_args)
-
-generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
-response = tokenizer.batch_decode(generate_ids, skip_special_tokens=True)[0]
-
-```
-
-## Running Model Inference with [OpenVINO GenAI](https://github.com/openvinotoolkit/openvino.genai)
-
-1. Install packages required for using OpenVINO GenAI.
-```
-pip install --pre -U --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/pre-release openvino openvino-tokenizers openvino-genai
-
-pip install huggingface_hub
-```
-
-2. Download model from HuggingFace Hub
-   
-```
-import huggingface_hub as hf_hub
-
-model_id = "OpenVINO/InternVL2-1B-int8-ov"
-model_path = "InternVL2-1B-int8-ov"
-
-hf_hub.snapshot_download(model_id, local_dir=model_path)
-
-```
-
-1. Run model inference:
-
-```
-import openvino_genai as ov_genai
-import requests
-from PIL import Image
-from io import BytesIO
-import numpy as np
-import openvino as ov
-
-device = "CPU"
-pipe = ov_genai.VLMPipeline(model_path, device)
-
-def load_image(image_file):
-    if isinstance(image_file, str) and (image_file.startswith("http") or image_file.startswith("https")):
-        response = requests.get(image_file)
-        image = Image.open(BytesIO(response.content)).convert("RGB")
-    else:
-        image = Image.open(image_file).convert("RGB")
-    image_data = np.array(image.getdata()).reshape(1, image.size[1], image.size[0], 3).astype(np.byte)
-    return ov.Tensor(image_data)
-
-prompt = "What is unusual on this picture?"
-
-url = "https://github.com/openvinotoolkit/openvino_notebooks/assets/29454499/d5fbbd1a-d484-415c-88cb-9986625b7b11"
-image_tensor = load_image(url)
-
-def streamer(subword: str) -> bool:
-    print(subword, end="", flush=True)
-    return False
-
-pipe.start_chat()
-output = pipe.generate(prompt, image=image_tensor, max_new_tokens=100, streamer=streamer)
-pipe.finish_chat()
-```
-
-More GenAI usage examples can be found in OpenVINO GenAI library [docs](https://github.com/openvinotoolkit/openvino.genai/blob/master/src/README.md) and [samples](https://github.com/openvinotoolkit/openvino.genai?tab=readme-ov-file#openvino-genai-samples)
-
-
-## Limitations
-
-
-Check the original [model card](https://huggingface.co/OpenGVLab/InternVL2-1B) for limitations.
-
-## Legal information
-
-The original model is distributed under [MIT](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/mit.md) license. More details can be found in [original model card](https://huggingface.co/OpenGVLab/InternVL2-1B).
-