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
```

theworker02 commited on 4 days ago

Commit

cf1c9f2

verified ·

1 Parent(s): 2e526ba

Document 13.9M CPU medium model card

Browse files

Files changed (1) hide show

README.md +22 -13

README.md CHANGED Viewed

@@ -12,24 +12,33 @@ datasets:
 base_model: gpt2-scratch
 ---
-# Open Reason open-reason-medium (CPU)
-This is a **medium** GPT-2-style causal LM trained from scratch on the Open Reason SFT split. It is larger than `theworker02/open-reason-small` and is **not** a 1B model and is **not** `theworker02/open-reason-1b`.
-- Parameters: 13867008
-- Architecture: n_layer=6 n_embd=384 n_head=6
-- Steps: 180
-- Backend: cpu-host
-- CUDA used: False
-- Hardware: CPU (Docker when available). AMD GPU is not used.
-- Dataset: theworker02/open-reason pipeline 1.4.0
-- SFT rows: 3175
-- Final loss: 4.416327476501465
-No Reddit sources. Project license Apache-2.0.
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 tok = AutoTokenizer.from_pretrained("theworker02/open-reason-medium")
 model = AutoModelForCausalLM.from_pretrained("theworker02/open-reason-medium")
 ```

 base_model: gpt2-scratch
 ---
+# Open Reason medium (CPU)
+A **medium** GPT-2-style causal LM trained from scratch on
+[`theworker02/open-reason`](https://huggingface.co/datasets/theworker02/open-reason)
+pipeline **v1.4.0**. It is larger than
+[`theworker02/open-reason-small`](https://huggingface.co/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 |
 ```python
 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`](https://huggingface.co/theworker02/open-reason-small).
+Dataset: [`theworker02/open-reason`](https://huggingface.co/datasets/theworker02/open-reason).
+Code: [`theworker02/open-reason`](https://github.com/theworker02/open-reason).