Instructions to use Open-Foundation-Models/PolyNorm_1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Open-Foundation-Models/PolyNorm_1B with Transformers:

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

pipe = pipeline("text-generation", model="Open-Foundation-Models/PolyNorm_1B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Open-Foundation-Models/PolyNorm_1B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Open-Foundation-Models/PolyNorm_1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Open-Foundation-Models/PolyNorm_1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Open-Foundation-Models/PolyNorm_1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Open-Foundation-Models/PolyNorm_1B

SGLang

How to use Open-Foundation-Models/PolyNorm_1B 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 "Open-Foundation-Models/PolyNorm_1B" \
    --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": "Open-Foundation-Models/PolyNorm_1B",
		"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 "Open-Foundation-Models/PolyNorm_1B" \
        --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": "Open-Foundation-Models/PolyNorm_1B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Open-Foundation-Models/PolyNorm_1B with Docker Model Runner:
```
docker model run hf.co/Open-Foundation-Models/PolyNorm_1B
```

Add pipeline tag: text-generation

by nielsr HF Staff - opened Mar 24, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+47

-46

nielsr

Mar 24, 2025

This PR adds the pipeline_tag: text-generation to the model card metadata. This tag is crucial for discoverability on the Hugging Face Hub, allowing researchers to easily find this model when searching for text generation models.

Add pipeline tag: text-generationffbf9b5c

BryceZhuo changed pull request status to merged Apr 1, 2025

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