Instructions to use noamaan6688/OutModelPolicy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use noamaan6688/OutModelPolicy with Transformers:

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

pipe = pipeline("text-generation", model="noamaan6688/OutModelPolicy")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("noamaan6688/OutModelPolicy")
model = AutoModelForCausalLM.from_pretrained("noamaan6688/OutModelPolicy")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use noamaan6688/OutModelPolicy with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "noamaan6688/OutModelPolicy"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "noamaan6688/OutModelPolicy",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/noamaan6688/OutModelPolicy

SGLang

How to use noamaan6688/OutModelPolicy 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 "noamaan6688/OutModelPolicy" \
    --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": "noamaan6688/OutModelPolicy",
		"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 "noamaan6688/OutModelPolicy" \
        --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": "noamaan6688/OutModelPolicy",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use noamaan6688/OutModelPolicy with Docker Model Runner:
```
docker model run hf.co/noamaan6688/OutModelPolicy
```

noamaan6688 commited on Apr 10, 2025

Commit

19b9180

verified ·

1 Parent(s): 4ac54c7

Training in progress, step 360

Browse files

Files changed (3) hide show

model.safetensors +1 -1
runs/Apr10_08-23-20_1f2beab41daa/events.out.tfevents.1744273421.1f2beab41daa.31.0 +3 -0
training_args.bin +1 -1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6678b61bf0c676afa2a2e2a06ac5cd59d266267a1d71038a77a98d697d200062
 size 2236892304

 version https://git-lfs.github.com/spec/v1
+oid sha256:14cb2aa6ddcbe1b6811e025d1a4b2554af986e465e499611c5dbc00bf519a648
 size 2236892304

runs/Apr10_08-23-20_1f2beab41daa/events.out.tfevents.1744273421.1f2beab41daa.31.0 ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:ba5dea678f7e36f4febe441f8a8bc068b69ae390bc5a3e274580e7704e3dae02
+size 5453

training_args.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:de1b578bb2c436f262d05bc49fb69e9a378b4ee612389b351021dc95b0b7bdbf
 size 5304

 version https://git-lfs.github.com/spec/v1
+oid sha256:56d62b8b891e5987bbc5a1de50a3a0f36e8287fbcbcda79a6fd0c22320a43982
 size 5304