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 / train_metrics.json

theworker02

Upload Open Reason CPU causal LM theworker02/open-reason-xl (not 1B)

9b47349 verified about 1 month ago

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	{
	"smoke": false,
	"cuda": false,
	"backend": "cpu-host",
	"architecture": "gpt2-scratch",
	"param_count": 443719680,
	"n_layer": 22,
	"n_embd": 1280,
	"n_head": 20,
	"vocab_size": 8192,
	"max_seq_len": 256,
	"steps": 120,
	"requested_steps": 120,
	"gradient_checkpointing": true,
	"gradient_accumulation": 2,
	"batch_size": 1,
	"learning_rate": 0.0003,
	"rows": 3175,
	"dataset_version": "1.4.0",
	"final_loss": 5.811557769775391,
	"losses_tail": [
	6.735813140869141,
	5.894803047180176,
	5.694976806640625,
	6.798207759857178,
	6.259979724884033,
	5.799972057342529,
	6.757445335388184,
	6.014622211456299,
	6.114091396331787,
	5.811557769775391
	],
	"hub_id_if_uploaded": "theworker02/open-reason-xl",
	"card_title": "Open Reason open-reason-xl (CPU)",
	"size_note": "This is an XL GPT-2-style causal LM (~450M parameters) trained from scratch on the Open Reason SFT split. It is larger than `theworker02/open-reason-large` and is not a 1B model and is not `theworker02/open-reason-1b`.",
	"hardware": "Host CPU (AMD64 Family 26 Model 68 Stepping 0, AuthenticAMD); 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."
	}