Instructions to use theworker02/open-reason-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use theworker02/open-reason-medium with Transformers:

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

pipe = pipeline("text-generation", model="theworker02/open-reason-medium")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("theworker02/open-reason-medium")
model = AutoModelForCausalLM.from_pretrained("theworker02/open-reason-medium", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use theworker02/open-reason-medium with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "theworker02/open-reason-medium"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "theworker02/open-reason-medium",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/theworker02/open-reason-medium

SGLang

How to use theworker02/open-reason-medium 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 "theworker02/open-reason-medium" \
    --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": "theworker02/open-reason-medium",
		"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 "theworker02/open-reason-medium" \
        --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": "theworker02/open-reason-medium",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use theworker02/open-reason-medium with Docker Model Runner:
```
docker model run hf.co/theworker02/open-reason-medium
```

Open Reason medium (CPU)

A medium GPT-2-style causal LM trained from scratch on theworker02/open-reason pipeline v1.4.0. It is larger than theworker02/open-reason-small (~1.3M) and is not a 1B model. Do not confuse it with theworker02/open-reason-1b.


Parameters	13,867,008
Architecture	GPT-2 scratch, `n_layer=6`, `n_embd=384`, `n_head=6`, vocab 8192, context 192
Steps	180
Batch size	2
Hardware	Host CPU (`torch` 2.12.0+cpu). Docker was not installed. AMD GPU was not used. CUDA: false
Dataset	`theworker02/open-reason` v1.4.0, 3175 SFT rows (`all` split)
Final loss	4.416
License	Apache-2.0
Reddit	Never used as a source

from transformers import AutoModelForCausalLM, AutoTokenizer

tok = AutoTokenizer.from_pretrained("theworker02/open-reason-medium")
model = AutoModelForCausalLM.from_pretrained("theworker02/open-reason-medium")

Companion small model: theworker02/open-reason-small. Dataset: theworker02/open-reason. Code: theworker02/open-reason.

Downloads last month: 164

Safetensors

Model size

13.9M params

Tensor type

F32

theworker02
/

open-reason-medium

Open Reason medium (CPU)

Dataset used to train theworker02/open-reason-medium