Instructions to use g8a9/vit-geppetto-captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use g8a9/vit-geppetto-captioning with Transformers:

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

pipe = pipeline("image-text-to-text", model="g8a9/vit-geppetto-captioning")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("g8a9/vit-geppetto-captioning")
model = AutoModelForMultimodalLM.from_pretrained("g8a9/vit-geppetto-captioning")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use g8a9/vit-geppetto-captioning with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "g8a9/vit-geppetto-captioning"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "g8a9/vit-geppetto-captioning",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/g8a9/vit-geppetto-captioning

SGLang

How to use g8a9/vit-geppetto-captioning 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 "g8a9/vit-geppetto-captioning" \
    --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": "g8a9/vit-geppetto-captioning",
		"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 "g8a9/vit-geppetto-captioning" \
        --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": "g8a9/vit-geppetto-captioning",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use g8a9/vit-geppetto-captioning with Docker Model Runner:
```
docker model run hf.co/g8a9/vit-geppetto-captioning
```

vit-geppetto-captioning / tokenizer_config.json

g8a9

Add initial checkpoint (6 epochs)

7f05a9f over 4 years ago

Raw

History Blame Contribute Delete

766 Bytes

{"unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "special_tokens_map_file": "/home/gattanasio/.cache/huggingface/transformers/4ff48f5a2f49a46881b77a5686cfecaba8d3bc8fb924afee9f3d0a0dfcc304dc.3ae9ae72462581d20e36bc528e9c47bb30cd671bb21add40ca0b24a0be9fac22", "name_or_path": "LorenzoDeMattei/GePpeTto", "errors": "replace", "tokenizer_class": "GPT2Tokenizer"}