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

Libraries

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

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

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

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "theworker02/open-reason-large"
# 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-large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

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

SGLang

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

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

open-reason-large

File size: 1,278 Bytes

33b53d8

{
  "smoke": false,
  "cuda": false,
  "backend": "cpu-host",
  "architecture": "gpt2-scratch",
  "param_count": 91544064,
  "n_layer": 12,
  "n_embd": 768,
  "n_head": 12,
  "vocab_size": 8192,
  "max_seq_len": 256,
  "steps": 400,
  "rows": 3175,
  "dataset_version": "1.4.0",
  "final_loss": 5.73606538772583,
  "losses_tail": [
    5.587280750274658,
    5.309240341186523,
    4.810147285461426,
    4.649975776672363,
    4.291345596313477,
    4.592579364776611,
    5.473930358886719,
    6.1341753005981445,
    5.86303186416626,
    5.73606538772583
  ],
  "hub_id_if_uploaded": "theworker02/open-reason-large",
  "card_title": "Open Reason open-reason-large (CPU)",
  "size_note": "This is a **large** GPT-2-style causal LM trained from scratch on the Open Reason SFT split. It is larger than `theworker02/open-reason-medium` and is **not** a 1B model and is **not** `theworker02/open-reason-1b`.",
  "hardware": "Host CPU; torch 2.12.0+cpu; cuda_available=False; docker_installed=False; docker_used=False. NVIDIA CUDA was not used. AMD GPU/ROCm/DirectML were not used.",
  "docker_used": false,
  "docker_installed": false,
  "torch_version": "2.12.0+cpu",
  "note": "CPU causal LM. Not open-reason-1b. Not AMD GPU. No Reddit."
}