Mono-InternVL-2B-S1-2

69
1
2.0B
2 languages
license:mit
by
OpenGVLab
Image Model
OTHER
2B params
New
69 downloads
Early-stage
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
5GB+ RAM
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
2GB+ RAM

Code Examples

python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
python
from lmdeploy import pipeline
from lmdeploy.vl import load_image

image = load_image('./examples/image1.jpg')
pipe = pipeline('OpenGVLab/Mono-InternVL-2B')
response = pipe(('Please describe the image shortly.', image))
print(response.text)
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
git clone https://github.com/OpenGVLab/Mono-InternVL.git
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
conda create -n monointernvl python=3.9 -y
  conda activate monointernvl
bash
pip install -r requirements.txt
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pip install -r requirements.txt
bash
pip install -r requirements.txt
bash
pip install -r requirements.txt
bash
pip install -r requirements.txt
bash
pip install -r requirements.txt
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pip install -r requirements.txt
bash
pip install -r requirements.txt
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pip install -r requirements.txt
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pip install -r requirements.txt
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pip install flash-attn==2.5.6 --no-build-isolation
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pip install flash-attn==2.5.6 --no-build-isolation
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pip install flash-attn==2.5.6 --no-build-isolation
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pip install flash-attn==2.5.6 --no-build-isolation
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pip install flash-attn==2.5.6 --no-build-isolation
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pip install flash-attn==2.5.6 --no-build-isolation
bash
pip install flash-attn==2.5.6 --no-build-isolation
bash
pip install flash-attn==2.5.6 --no-build-isolation
bash
pip install flash-attn==2.5.6 --no-build-isolation
bash
pip install flash-attn==2.5.6 --no-build-isolation
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
bash
git clone https://github.com/Dao-AILab/flash-attention.git
  cd flash-attention
  git checkout v2.5.6
  python setup.py install
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
LLaVA-v1.5-mix665k Datasetbash
mkdir playground
wget https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K/resolve/main/llava_v1_5_mix665k.json -P playground/
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1
pip install -U huggingface_hubbash
mkdir workdirs
cd workdirs/
# pip install -U huggingface_hub
huggingface-cli download --resume-download --local-dir-use-symlinks False OpenGVLab/Mono-InternVL-2B-S1-1 --local-dir Mono-InternVL-2B-S1-1

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