Instructions to use Gustavosta/MagicPrompt-Stable-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gustavosta/MagicPrompt-Stable-Diffusion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gustavosta/MagicPrompt-Stable-Diffusion")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Gustavosta/MagicPrompt-Stable-Diffusion") model = AutoModelForCausalLM.from_pretrained("Gustavosta/MagicPrompt-Stable-Diffusion") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Gustavosta/MagicPrompt-Stable-Diffusion with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gustavosta/MagicPrompt-Stable-Diffusion" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gustavosta/MagicPrompt-Stable-Diffusion", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Gustavosta/MagicPrompt-Stable-Diffusion
- SGLang
How to use Gustavosta/MagicPrompt-Stable-Diffusion 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 "Gustavosta/MagicPrompt-Stable-Diffusion" \ --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": "Gustavosta/MagicPrompt-Stable-Diffusion", "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 "Gustavosta/MagicPrompt-Stable-Diffusion" \ --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": "Gustavosta/MagicPrompt-Stable-Diffusion", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Gustavosta/MagicPrompt-Stable-Diffusion with Docker Model Runner:
docker model run hf.co/Gustavosta/MagicPrompt-Stable-Diffusion
Add Core ML conversion
#8
by alandaoEV - opened
- coreml/text-generation/float16_model.mlpackage/Data/com.apple.CoreML/model.mlmodel +3 -0
- coreml/text-generation/float16_model.mlpackage/Data/com.apple.CoreML/weights/weight.bin +3 -0
- coreml/text-generation/float16_model.mlpackage/Manifest.json +18 -0
- coreml/text-generation/float32_model.mlpackage/Data/com.apple.CoreML/model.mlmodel +3 -0
- coreml/text-generation/float32_model.mlpackage/Data/com.apple.CoreML/weights/weight.bin +3 -0
- coreml/text-generation/float32_model.mlpackage/Manifest.json +18 -0
coreml/text-generation/float16_model.mlpackage/Data/com.apple.CoreML/model.mlmodel
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c11ada6303fa754107df0f4ce948bf7e7d0c1fd645f47b51da796c2ab156a89a
|
| 3 |
+
size 2492186
|
coreml/text-generation/float16_model.mlpackage/Data/com.apple.CoreML/weights/weight.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:69aca025e9227d93d8301978c30d40b71ef041d9fdb16f38c24ee1cd3d3ddf05
|
| 3 |
+
size 334246242
|
coreml/text-generation/float16_model.mlpackage/Manifest.json
ADDED
|
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"fileFormatVersion": "1.0.0",
|
| 3 |
+
"itemInfoEntries": {
|
| 4 |
+
"33C17585-DF5B-4B29-A87B-1F625E9ECE72": {
|
| 5 |
+
"author": "com.apple.CoreML",
|
| 6 |
+
"description": "CoreML Model Specification",
|
| 7 |
+
"name": "model.mlmodel",
|
| 8 |
+
"path": "com.apple.CoreML/model.mlmodel"
|
| 9 |
+
},
|
| 10 |
+
"A5E1F6D5-9D14-4CC8-A3ED-6005B33D638D": {
|
| 11 |
+
"author": "com.apple.CoreML",
|
| 12 |
+
"description": "CoreML Model Weights",
|
| 13 |
+
"name": "weights",
|
| 14 |
+
"path": "com.apple.CoreML/weights"
|
| 15 |
+
}
|
| 16 |
+
},
|
| 17 |
+
"rootModelIdentifier": "33C17585-DF5B-4B29-A87B-1F625E9ECE72"
|
| 18 |
+
}
|
coreml/text-generation/float32_model.mlpackage/Data/com.apple.CoreML/model.mlmodel
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:29b3d9e3e7ee010d1fca94d27dcc00f9fdb9641825e3bf12a628e98e18c8f986
|
| 3 |
+
size 2477339
|
coreml/text-generation/float32_model.mlpackage/Data/com.apple.CoreML/weights/weight.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:dfdd46bbf16743814840f1167caaa00d5997a1a5cf8bead3ddb34f405727fb74
|
| 3 |
+
size 659044868
|
coreml/text-generation/float32_model.mlpackage/Manifest.json
ADDED
|
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"fileFormatVersion": "1.0.0",
|
| 3 |
+
"itemInfoEntries": {
|
| 4 |
+
"53FB6ADB-5022-4B6E-AC17-A8698C7BB13B": {
|
| 5 |
+
"author": "com.apple.CoreML",
|
| 6 |
+
"description": "CoreML Model Weights",
|
| 7 |
+
"name": "weights",
|
| 8 |
+
"path": "com.apple.CoreML/weights"
|
| 9 |
+
},
|
| 10 |
+
"64093EBE-683E-4E2A-89F9-E2E84A638876": {
|
| 11 |
+
"author": "com.apple.CoreML",
|
| 12 |
+
"description": "CoreML Model Specification",
|
| 13 |
+
"name": "model.mlmodel",
|
| 14 |
+
"path": "com.apple.CoreML/model.mlmodel"
|
| 15 |
+
}
|
| 16 |
+
},
|
| 17 |
+
"rootModelIdentifier": "64093EBE-683E-4E2A-89F9-E2E84A638876"
|
| 18 |
+
}
|