Visual Question Answering
Transformers
Safetensors
PyTorch
English
tinyllava
text-generation
vision-language
custom_code
Eval Results (legacy)
Instructions to use keeeeenw/MicroLlava with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keeeeenw/MicroLlava with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="keeeeenw/MicroLlava", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("keeeeenw/MicroLlava", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
364e925 | 1 2 3 4 5 6 7 8 | {
"_from_model_config": true,
"bos_token_id": 1,
"eos_token_id": 2,
"transformers_version": "4.40.1",
"use_cache": false
}
|