Instructions to use cemde/Domain-Certification-MedQA-Guide-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cemde/Domain-Certification-MedQA-Guide-Base with Transformers:

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

pipe = pipeline("text-generation", model="cemde/Domain-Certification-MedQA-Guide-Base")

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("cemde/Domain-Certification-MedQA-Guide-Base")
model = AutoModel.from_pretrained("cemde/Domain-Certification-MedQA-Guide-Base", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cemde/Domain-Certification-MedQA-Guide-Base with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/cemde/Domain-Certification-MedQA-Guide-Base

SGLang

How to use cemde/Domain-Certification-MedQA-Guide-Base 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 "cemde/Domain-Certification-MedQA-Guide-Base" \
    --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": "cemde/Domain-Certification-MedQA-Guide-Base",
		"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 "cemde/Domain-Certification-MedQA-Guide-Base" \
        --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": "cemde/Domain-Certification-MedQA-Guide-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use cemde/Domain-Certification-MedQA-Guide-Base with Docker Model Runner:
```
docker model run hf.co/cemde/Domain-Certification-MedQA-Guide-Base
```

cemde commited on May 11, 2025

Commit

287019a

verified ·

1 Parent(s): 015ccb1

Update model card

Browse files

Files changed (1) hide show

README.md +5 -6

README.md CHANGED Viewed

@@ -1,16 +1,16 @@
 ---
-datasets:
-- qiaojin/PubMedQA
 language:
 - en
-library_name: transformers
 license: apache-2.0
 pipeline_tag: text-generation
 tags:
 - Domain-Certification
 - Jailbreaking
 - Adversarial-Attack
 - Guardrail
 ---
 # Shh, don't say that! Domain Certification in LLMs
@@ -30,9 +30,8 @@ We provide the guide models for our Medical Question Answering experiments.
 | Model | Description |
 | - | - |
-| cemde/Domain-Certification-MedQA-Guide-Base | This is the base model trained on the ground-truth responses. |
-| cemde/Domain-Certification-MedQA-Guide-Finetuned | This is the model trained on responses from Llama-3-8B. |
 ## Citation

 ---
 language:
 - en
 license: apache-2.0
+library_name: transformers
 pipeline_tag: text-generation
 tags:
 - Domain-Certification
 - Jailbreaking
 - Adversarial-Attack
 - Guardrail
+datasets:
+- qiaojin/PubMedQA
 ---
 # Shh, don't say that! Domain Certification in LLMs
 | Model | Description |
 | - | - |
+| [cemde/Domain-Certification-MedQA-Guide-Base](https://huggingface.co/cemde/Domain-Certification-MedQA-Guide-Base) | This is the base model trained on the ground-truth responses. |
+| [cemde/Domain-Certification-MedQA-Guide-Finetuned](https://huggingface.co/cemde/Domain-Certification-MedQA-Guide-Finetuned) | This is the model trained on responses from Llama-3-8B. |
 ## Citation