Instructions to use flanara/physics-mcq-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use flanara/physics-mcq-generator with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2")
model = PeftModel.from_pretrained(base_model, "flanara/physics-mcq-generator")

Transformers

How to use flanara/physics-mcq-generator with Transformers:

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

pipe = pipeline("text-generation", model="flanara/physics-mcq-generator")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("flanara/physics-mcq-generator", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use flanara/physics-mcq-generator with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/flanara/physics-mcq-generator

SGLang

How to use flanara/physics-mcq-generator 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 "flanara/physics-mcq-generator" \
    --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": "flanara/physics-mcq-generator",
		"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 "flanara/physics-mcq-generator" \
        --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": "flanara/physics-mcq-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use flanara/physics-mcq-generator with Docker Model Runner:
```
docker model run hf.co/flanara/physics-mcq-generator
```

flanara commited on Sep 6, 2025

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@@ -24,7 +24,7 @@ A fine-tuned language model that generates high-quality physics multiple-choice
 This model is specifically designed to generate competitive physics multiple-choice questions with accurate content, plausible distractors, and appropriate difficulty levels for entrance exam preparation. It supports four cognitive skill levels (Recall, Application, Analysis, Evaluation) and excels across major physics domains including mechanics, electromagnetism, thermodynamics, optics, and modern physics.
-- **Developed by:** [Your Name/Organization]
 - **Model type:** Fine-tuned Causal Language Model
 - **Language(s) (NLP):** English
 - **License:** MIT
@@ -32,8 +32,8 @@ This model is specifically designed to generate competitive physics multiple-cho
 ### Model Sources
-- **Repository:** https://huggingface.co/your_username/physics-mcq-generator
-- **Demo:** [Available as Hugging Face Space]
 ## Uses

 This model is specifically designed to generate competitive physics multiple-choice questions with accurate content, plausible distractors, and appropriate difficulty levels for entrance exam preparation. It supports four cognitive skill levels (Recall, Application, Analysis, Evaluation) and excels across major physics domains including mechanics, electromagnetism, thermodynamics, optics, and modern physics.
+- **Developed by:** [flanara]
 - **Model type:** Fine-tuned Causal Language Model
 - **Language(s) (NLP):** English
 - **License:** MIT
 ### Model Sources
+- **Repository:** https://huggingface.co/flanara/physics-mcq-generator
 ## Uses