metadata

base_model: google/paligemma-3b-pt-224
library_name: peft
license: gemma
tags:
  - generated_from_trainer
model-index:
  - name: paligemma_vqav3
    results: []

Inference

model_id = "Ohmmy3847/paligemma_vqav3"
model = PaliGemmaForConditionalGeneration.from_pretrained("Ohmmy3847/paligemma_vqav3")
processor = AutoProcessor.from_pretrained("google/paligemma-3b-pt-224")
prompt = "อธิบายภาพนี้เป็นภาษาไทย"

raw_image = Image.open("<Your Image>.jpg")

inputs = processor(prompt, raw_image.convert("RGB"), return_tensors="pt")
output = model.generate(**inputs, max_new_tokens=20)

print(processor.decode(output[0], skip_special_tokens=True)[len(prompt):])
raw_image

paligemma_vqav3

This model is a fine-tuned version of google/paligemma-3b-pt-224 on an unknown dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
num_epochs: 2

Training results

Framework versions

PEFT 0.11.2.dev0
Transformers 4.42.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1