Instructions to use MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit with Transformers:

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

pipe = pipeline("text-generation", model="MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit")
model = AutoModelForCausalLM.from_pretrained("MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit

SGLang

How to use MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit 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 "MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit" \
    --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": "MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit",
		"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 "MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit" \
        --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": "MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Unsloth Desktop
Docker Model Runner
How to use MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit with Docker Model Runner:
```
docker model run hf.co/MasterControlAIML/Qwen2.5-7b-Answer-Distractor-MCQ-Generation-merged-16bit
```

bhaviktheslider commited on Jan 31, 2025

Commit

e673f30

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1 Parent(s): 70a9c95

Update README.md

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@@ -10,6 +10,8 @@ tags:
 license: apache-2.0
 language:
 - en
 ---
 # Uploaded  model
@@ -54,4 +56,4 @@ Distractors: Increasing transaminases,Increasing bilirubin,Increasing prothrombi
 This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

 license: apache-2.0
 language:
 - en
+datasets:
+- MasterControlAIML/Medmcqa-For-FinetuningQwen
 ---
 # Uploaded  model
 This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)