Instructions to use OpenMOSE/HRWKV7-Reka-Flash3-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenMOSE/HRWKV7-Reka-Flash3-Preview with Transformers:

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

pipe = pipeline("text-generation", model="OpenMOSE/HRWKV7-Reka-Flash3-Preview")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("OpenMOSE/HRWKV7-Reka-Flash3-Preview", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use OpenMOSE/HRWKV7-Reka-Flash3-Preview with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OpenMOSE/HRWKV7-Reka-Flash3-Preview"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OpenMOSE/HRWKV7-Reka-Flash3-Preview",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/OpenMOSE/HRWKV7-Reka-Flash3-Preview

SGLang

How to use OpenMOSE/HRWKV7-Reka-Flash3-Preview 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 "OpenMOSE/HRWKV7-Reka-Flash3-Preview" \
    --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": "OpenMOSE/HRWKV7-Reka-Flash3-Preview",
		"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 "OpenMOSE/HRWKV7-Reka-Flash3-Preview" \
        --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": "OpenMOSE/HRWKV7-Reka-Flash3-Preview",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OpenMOSE/HRWKV7-Reka-Flash3-Preview with Docker Model Runner:
```
docker model run hf.co/OpenMOSE/HRWKV7-Reka-Flash3-Preview
```

OpenMOSE commited on Jul 6, 2025

Commit

e37f8bd

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1 Parent(s): 88fb0d7

Update README.md

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@@ -9,7 +9,7 @@ license: apache-2.0
 > I'm simply exploring the possibility of linearizing existing Transformer models.
 > It's still far from perfect,
-> but I hope you'll bear with me as I continue this journey.
 ### Model Description
@@ -88,7 +88,11 @@ curl http://127.0.0.1:9000/loadmodel -X POST -H "Content-Type: application/json"
 ```
 ## Thank you for Big help :)
-- SmerkyG Inspired by RADLADS (https://arxiv.org/abs/2505.03005)
 ## Model Card Contact

 > I'm simply exploring the possibility of linearizing existing Transformer models.
 > It's still far from perfect,
+> but I hope you'll bear with me as I continue this journey. :)
 ### Model Description
 ```
 ## Thank you for Big help :)
+- SmerkyG Inspired by RADLADS (https://arxiv.org/abs/2505.03005)
+- https://github.com/recursal/RADLADS-paper
+## Training Code
+- https://github.com/OpenMOSE/RWKVInside (still buggy)
 ## Model Card Contact