Visual Question Answering
Transformers
PyTorch
internlm2
feature-extraction
custom_code
4-bit precision
awq
Instructions to use internlm/internlm-xcomposer2d5-7b-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/internlm-xcomposer2d5-7b-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="internlm/internlm-xcomposer2d5-7b-4bit", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("internlm/internlm-xcomposer2d5-7b-4bit", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Triton error when running the transformers version
1
#6 opened about 1 year ago
by
frutiemax
Adding `safetensors` variant of this model
#5 opened almost 2 years ago
by
SFconvertbot
Create README.md
#3 opened about 2 years ago
by
zhougongkai
Adding `safetensors` variant of this model
#2 opened about 2 years ago
by
SFconvertbot
When was the last time?
#1 opened about 2 years ago
by
vanch007