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 / README.md

theworker02

Polish large CPU model card (91,544,064 params, host CPU, not 1B)

05c7782 verified 5 days ago

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metadata

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 large (CPU)

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 (13,867,008 parameters) and is not a 1B model and is not theworker02/open-reason-1b.

Weights live on this Hub repo. They are not stored in the GitHub git tree.

Training facts

Parameters: 91,544,064
Architecture: GPT-2-style from scratch; n_layer=12, n_embd=768, n_head=12, vocab_size=8192, max_seq_len=256
Steps: 400 (batch size 2)
Final training loss: 5.7361 (next-token NLL on training batches; not a benchmark score)
SFT rows: 3,175 from data/release/all.jsonl
Dataset: theworker02/open-reason pipeline 1.4.0
License: Apache-2.0
Hardware: AMD Ryzen 9 9950X host CPU; torch 2.12.0+cpu; torch.cuda.is_available()=False; Docker not installed and not used; nvidia-smi not present. NVIDIA CUDA was not used. AMD GPU / ROCm / DirectML were not used.

Dataset: https://huggingface.co/datasets/theworker02/open-reason
Small (~1.3M): https://huggingface.co/theworker02/open-reason-small
Medium (13,867,008): https://huggingface.co/theworker02/open-reason-medium
Large (this repo, 91,544,064): https://huggingface.co/theworker02/open-reason-large
GitHub: https://github.com/theworker02/open-reason

No Reddit sources.

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

theworker02
/

open-reason-large

Open Reason large (CPU)

Training facts

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