Instructions to use ahmedesmail16/image-caption-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ahmedesmail16/image-caption-generator with Transformers:

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

pipe = pipeline("image-text-to-text", model="ahmedesmail16/image-caption-generator")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("ahmedesmail16/image-caption-generator")
model = AutoModelForMultimodalLM.from_pretrained("ahmedesmail16/image-caption-generator", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ahmedesmail16/image-caption-generator with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ahmedesmail16/image-caption-generator"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ahmedesmail16/image-caption-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ahmedesmail16/image-caption-generator

SGLang

How to use ahmedesmail16/image-caption-generator 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 "ahmedesmail16/image-caption-generator" \
    --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": "ahmedesmail16/image-caption-generator",
		"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 "ahmedesmail16/image-caption-generator" \
        --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": "ahmedesmail16/image-caption-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ahmedesmail16/image-caption-generator with Docker Model Runner:
```
docker model run hf.co/ahmedesmail16/image-caption-generator
```

ahmedesmail16 commited on Mar 20, 2024

Commit

0793a16

verified ·

1 Parent(s): 0568cd3

Training in progress, epoch 4

Browse files

Files changed (2) hide show

model.safetensors +1 -1
runs/Mar20_05-55-25_216479dcc1c5/events.out.tfevents.1710914143.216479dcc1c5.721.1 +2 -2

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c3575177e3ed8cf58ff51e2f02266a9a83ec4f843f805e1517a575542fdea1a7
 size 22686584

 version https://git-lfs.github.com/spec/v1
+oid sha256:64686daed576df2cd3207a66f8f81bdf4e4bbcf844cc19f1743c410906cb6e59
 size 22686584

runs/Mar20_05-55-25_216479dcc1c5/events.out.tfevents.1710914143.216479dcc1c5.721.1 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4b5324470e050c13d1f6d30690f3f6b70aae4718f0131a3f8e701e233ba54324
-size 82738

 version https://git-lfs.github.com/spec/v1
+oid sha256:a1b18f9180d5b739df3e698c8463af48fc5f38cf3bb41fb9c3dafd26b3c8ee5f
+size 83004