Instructions to use Ostgot/blip-base-codenrock-solution with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ostgot/blip-base-codenrock-solution with Transformers:

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

pipe = pipeline("image-text-to-text", model="Ostgot/blip-base-codenrock-solution")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("Ostgot/blip-base-codenrock-solution")
model = AutoModelForImageTextToText.from_pretrained("Ostgot/blip-base-codenrock-solution")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Ostgot/blip-base-codenrock-solution with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Ostgot/blip-base-codenrock-solution

SGLang

How to use Ostgot/blip-base-codenrock-solution 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 "Ostgot/blip-base-codenrock-solution" \
    --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": "Ostgot/blip-base-codenrock-solution",
		"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 "Ostgot/blip-base-codenrock-solution" \
        --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": "Ostgot/blip-base-codenrock-solution",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Ostgot/blip-base-codenrock-solution with Docker Model Runner:
```
docker model run hf.co/Ostgot/blip-base-codenrock-solution
```

Ostgot commited on Aug 24, 2023

Commit

1ecd28d

1 Parent(s): d350fef

Upload BlipForConditionalGeneration

Browse files

Files changed (2) hide show

config.json +3 -2
pytorch_model.bin +1 -1

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "Shamima/Blip-finetuned-sd-1k",
   "architectures": [
     "BlipForConditionalGeneration"
   ],
@@ -11,7 +11,8 @@
   "projection_dim": 512,
   "text_config": {
     "initializer_factor": 1.0,
-    "model_type": "blip_text_model"
   },
   "torch_dtype": "float32",
   "transformers_version": "4.33.0.dev0",

 {
+  "_name_or_path": "Salesforce/blip-image-captioning-base",
   "architectures": [
     "BlipForConditionalGeneration"
   ],
   "projection_dim": 512,
   "text_config": {
     "initializer_factor": 1.0,
+    "model_type": "blip_text_model",
+    "num_attention_heads": 12
   },
   "torch_dtype": "float32",
   "transformers_version": "4.33.0.dev0",

pytorch_model.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7011e024fb452d0a3d5cc643e80aa951ff15e2572d56a637218863c9d806b12f
 size 989823021

 version https://git-lfs.github.com/spec/v1
+oid sha256:4b6ab1d1a8d447df6f7a1e1402e09d9b73247093a195b03c5655384afbf250c6
 size 989823021