Instructions to use samim2024/Image-Text-To-Text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use samim2024/Image-Text-To-Text with Transformers:

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

pipe = pipeline("image-text-to-text", model="samim2024/Image-Text-To-Text")

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("samim2024/Image-Text-To-Text")
model = AutoModelForMultimodalLM.from_pretrained("samim2024/Image-Text-To-Text")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use samim2024/Image-Text-To-Text with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "samim2024/Image-Text-To-Text"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "samim2024/Image-Text-To-Text",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/samim2024/Image-Text-To-Text

SGLang

How to use samim2024/Image-Text-To-Text 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 "samim2024/Image-Text-To-Text" \
    --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": "samim2024/Image-Text-To-Text",
		"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 "samim2024/Image-Text-To-Text" \
        --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": "samim2024/Image-Text-To-Text",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use samim2024/Image-Text-To-Text with Docker Model Runner:
```
docker model run hf.co/samim2024/Image-Text-To-Text
```

samim2024 commited on Jun 7, 2024

Commit

100eadb

verified ·

1 Parent(s): 739fdd3

Upload config

Browse files

Files changed (1) hide show

adapter_config.json +2 -5

adapter_config.json CHANGED Viewed

@@ -1,13 +1,10 @@
 {
   "alpha_pattern": {},
-  "auto_mapping": {
-    "base_model_class": "PeftModel",
-    "parent_library": "peft.peft_model"
-  },
   "base_model_name_or_path": null,
   "bias": "none",
   "fan_in_fan_out": false,
-  "inference_mode": true,
   "init_lora_weights": true,
   "layer_replication": null,
   "layers_pattern": null,

 {
   "alpha_pattern": {},
+  "auto_mapping": null,
   "base_model_name_or_path": null,
   "bias": "none",
   "fan_in_fan_out": false,
+  "inference_mode": false,
   "init_lora_weights": true,
   "layer_replication": null,
   "layers_pattern": null,