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---
base_model: qresearch/doubutsu-2b-pt-756
library_name: peft
license: apache-2.0
datasets:
- abhishek/vqa_small
---
# doubutsu-2b-lora-756-vqa
An adapter for [qresearch/doubutsu-2b-pt-756](https://huggingface.co/qresearch/doubutsu-2b-pt-756) trained on [vqa_small](https://huggingface.co/datasets/abhishek/vqa_small) for 3 epochs.
## Usage
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from PIL import Image
model_id = "qresearch/doubutsu-2b-pt-756"
model = AutoModelForCausalLM.from_pretrained(
model_id,
trust_remote_code=True,
torch_dtype=torch.float16,
).to("cuda")
tokenizer = AutoTokenizer.from_pretrained(
model_id,
use_fast=True,
)
model.load_adapter("qresearch/doubutsu-2b-lora-756-vqa")
image = Image.open("IMAGE")
print(
model.answer_question(
image, "Describe the image", tokenizer, max_new_tokens=128, temperature=0.1
),
)
```
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- batch_size: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- num_epochs: 3
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