Instructions to use ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2")
model = AutoModelForImageTextToText.from_pretrained("ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2

SGLang

How to use ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2 with Docker Model Runner:
```
docker model run hf.co/ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2
```

git-large-r-coco-IDB_ADv1_COCOv6-rv2

This model is a fine-tuned version of microsoft/git-large-r-coco on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0934
Meteor Score: {'meteor': 0.6849337864778346}

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: 3e-05
train_batch_size: 6
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 96
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_steps: 50
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Meteor Score
0.7802	5.0	5	0.1019	{'meteor': 0.6667354024231188}
0.756	10.0	10	0.1006	{'meteor': 0.6766394690979587}
0.7057	15.0	15	0.0972	{'meteor': 0.6774630113691023}
0.6349	20.0	20	0.0934	{'meteor': 0.6849337864778346}

Framework versions

Transformers 4.46.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.20.2

Downloads last month: 8

Safetensors

Model size

0.4B params

Tensor type

F32

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Image-Text-to-Text

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Model tree for ooliverz/git-large-r-coco-IDB_ADv1_COCOv6-rv2

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