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

Libraries

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

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

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

Install from pip and serve model

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

Use Docker

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

SGLang

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

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

open-reason-xl / README.md

theworker02

Honest XL model card: 443719680 params, 120 CPU steps, NLL 5.8116

df972ca verified 5 days ago

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	---
	language:
	- en
	license: apache-2.0
	library_name: transformers
	tags:
	- open-reason
	- causal-lm
	- cpu
	datasets:
	- theworker02/open-reason
	base_model: gpt2-scratch
	---

	# Open Reason XL (CPU)

	GPT-2-style causal LM trained from scratch on the Open Reason SFT split.
	Exact parameter count: 443,719,680. This is not a 1B model and is not
	`theworker02/open-reason-1b`.

	## Training facts

	- Parameters: 443,719,680 (`sum(p.numel() for p in model.parameters())`)
	- Architecture: n_layer=22, n_embd=1280, n_head=20, vocab=8192, seq=256
	- Steps: 120 (batch 1, gradient accumulation 2, gradient checkpointing)
	- Device: host CPU (AMD Ryzen 9 9950X, 32 threads)
	- `torch`: 2.12.0+cpu; `cuda_available=False`; Docker not installed
	- NVIDIA CUDA was not used. AMD GPU / ROCm / DirectML were not used
	- Dataset: [`theworker02/open-reason`](https://huggingface.co/datasets/theworker02/open-reason) pipeline 1.4.0
	- SFT rows: 3175 (`data/release/all.jsonl`)
	- Final training NLL: 5.8116
	- License: Apache-2.0
	- No held-out exact-match / coding / math benchmark scores are claimed

	Related checkpoints (none of these is a 1B model):

	- Dataset: https://huggingface.co/datasets/theworker02/open-reason
	- Small: https://huggingface.co/theworker02/open-reason-small
	- Medium: https://huggingface.co/theworker02/open-reason-medium
	- Large: https://huggingface.co/theworker02/open-reason-large
	- XL: https://huggingface.co/theworker02/open-reason-xl

	No Reddit sources. Project license Apache-2.0.

	```python
	from transformers import AutoModelForCausalLM, AutoTokenizer
	tok = AutoTokenizer.from_pretrained("theworker02/open-reason-xl")
	model = AutoModelForCausalLM.from_pretrained("theworker02/open-reason-xl")
	```