Instructions to use CodeSoft/MetaDiffusion-150M-exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CodeSoft/MetaDiffusion-150M-exp with Transformers:

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

pipe = pipeline("text-generation", model="CodeSoft/MetaDiffusion-150M-exp")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("CodeSoft/MetaDiffusion-150M-exp", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use CodeSoft/MetaDiffusion-150M-exp with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CodeSoft/MetaDiffusion-150M-exp"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CodeSoft/MetaDiffusion-150M-exp",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/CodeSoft/MetaDiffusion-150M-exp

SGLang

How to use CodeSoft/MetaDiffusion-150M-exp 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 "CodeSoft/MetaDiffusion-150M-exp" \
    --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": "CodeSoft/MetaDiffusion-150M-exp",
		"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 "CodeSoft/MetaDiffusion-150M-exp" \
        --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": "CodeSoft/MetaDiffusion-150M-exp",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use CodeSoft/MetaDiffusion-150M-exp with Docker Model Runner:
```
docker model run hf.co/CodeSoft/MetaDiffusion-150M-exp
```

CodeSoft commited on 7 days ago

Commit

96ef5f8

verified ·

1 Parent(s): 7bf4091

Update README.md

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README.md +14 -16

README.md CHANGED Viewed

@@ -1,24 +1,22 @@
 ---
 license: apache-2.0
 language:
-  - en
 pipeline_tag: text-generation
 library_name: transformers
 tags:
-  - metadiffusion
-  - diffusion-language-model
-  - diffusion
-  - transformer
-  - language-model
-  - autoregressive-conversion
-  - experimental
-  - research
-  - 150m
-  - english
 ---
 <h1 align="center">MetaDiffusion-150M-exp</h1>
@@ -133,4 +131,4 @@ This release is not instruction tuned and is not intended for production deploym
 ## Acknowledgements
-MetaDiffusion is derived from the Supra-1.5-50M-Base-exp model. Credit goes to the Supra authors for the original autoregressive checkpoint that served as the initialization for this work. MetaDiffusion is released under the Apache-2.0 license in accordance with the licensing terms of the original Supra checkpoint.

 ---
 license: apache-2.0
 language:
+- en
 pipeline_tag: text-generation
 library_name: transformers
 tags:
+- metadiffusion
+- diffusion-language-model
+- diffusion
+- transformer
+- language-model
+- autoregressive-conversion
+- experimental
+- research
+- 150m
+- english
+base_model:
+- SupraLabs/Supra-1.5-50M-Base-exp
 ---
 <h1 align="center">MetaDiffusion-150M-exp</h1>
 ## Acknowledgements
+MetaDiffusion is derived from the Supra-1.5-50M-Base-exp model. Credit goes to the Supra authors for the original autoregressive checkpoint that served as the initialization for this work. MetaDiffusion is released under the Apache-2.0 license in accordance with the licensing terms of the original Supra checkpoint.