Instructions to use analogllm/analog_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use analogllm/analog_model with Transformers:

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

pipe = pipeline("text-generation", model="analogllm/analog_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("analogllm/analog_model")
model = AutoModelForCausalLM.from_pretrained("analogllm/analog_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use analogllm/analog_model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "analogllm/analog_model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "analogllm/analog_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/analogllm/analog_model

SGLang

How to use analogllm/analog_model 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 "analogllm/analog_model" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "analogllm/analog_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "analogllm/analog_model" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "analogllm/analog_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use analogllm/analog_model with Docker Model Runner:
```
docker model run hf.co/analogllm/analog_model
```

Improve model card for AnalogSeeker_2025_07_10_3

by nielsr HF Staff - opened Aug 15, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+120

-9

nielsr

Aug 15, 2025

This PR significantly enhances the model card for AnalogSeeker_2025_07_10_3 by:

Adding the pipeline_tag: text-generation to ensure proper discoverability on the Hugging Face Hub.
Adding a specific analog-circuit-design tag to improve searchability within the domain.
Populating the "Model description", "Intended uses & limitations", and "Training and evaluation data" sections with comprehensive details extracted from the paper abstract.
Including direct links to the paper, the project page, and the GitHub repository.
Adding a practical Python code example for sample usage with the transformers library.
Including a BibTeX citation for proper academic attribution.

These updates provide users with a much clearer understanding of the model's purpose, functionality, and how to use it.

Improve model card for AnalogSeeker_2025_07_10_3ba2cf7e1

analogllm

Owner Aug 19, 2025

Thank you very much!

nielsr

Aug 19, 2025

Thanks! Any reason not to merge the PR?

analogllm changed pull request status to merged Aug 20, 2025

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