Instructions to use OpenPeerAI/My-Name-is-Riemann-Prerelease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OpenPeerAI/My-Name-is-Riemann-Prerelease with Transformers:

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

pipe = pipeline("text-generation", model="OpenPeerAI/My-Name-is-Riemann-Prerelease", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("OpenPeerAI/My-Name-is-Riemann-Prerelease", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OpenPeerAI/My-Name-is-Riemann-Prerelease with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/OpenPeerAI/My-Name-is-Riemann-Prerelease

SGLang

How to use OpenPeerAI/My-Name-is-Riemann-Prerelease 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 "OpenPeerAI/My-Name-is-Riemann-Prerelease" \
    --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": "OpenPeerAI/My-Name-is-Riemann-Prerelease",
		"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 "OpenPeerAI/My-Name-is-Riemann-Prerelease" \
        --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": "OpenPeerAI/My-Name-is-Riemann-Prerelease",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OpenPeerAI/My-Name-is-Riemann-Prerelease with Docker Model Runner:
```
docker model run hf.co/OpenPeerAI/My-Name-is-Riemann-Prerelease
```

Mentors4EDU commited on about 21 hours ago

Commit

9a031c4

verified ·

1 Parent(s): 6c49abb

Model card: link the three demo Spaces

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README.md +1 -0

README.md CHANGED Viewed

@@ -137,6 +137,7 @@ The model is named after Riemann Computing.
 - **Repository:** This Hugging Face repository (model weights, NTK controller, remote code, training pipeline)
 - **Base model:** [OpenPeerAI/OpenPeerLLM](https://huggingface.co/OpenPeerAI/OpenPeerLLM), DOI [10.57967/hf/6469](https://doi.org/10.57967/hf/6469)
 - **Fine-tuning method:** [OpenPeerAI/OpenPeer-AI-NTK-Trainer](https://huggingface.co/OpenPeerAI/OpenPeer-AI-NTK-Trainer) and [ntkmirror](https://github.com/leochlon/ntkmirror)
 ## Uses

 - **Repository:** This Hugging Face repository (model weights, NTK controller, remote code, training pipeline)
 - **Base model:** [OpenPeerAI/OpenPeerLLM](https://huggingface.co/OpenPeerAI/OpenPeerLLM), DOI [10.57967/hf/6469](https://doi.org/10.57967/hf/6469)
 - **Fine-tuning method:** [OpenPeerAI/OpenPeer-AI-NTK-Trainer](https://huggingface.co/OpenPeerAI/OpenPeer-AI-NTK-Trainer) and [ntkmirror](https://github.com/leochlon/ntkmirror)
+- **Demo:** [My Name is Riemann Prerelease - Basic Demo](https://huggingface.co/spaces/OpenPeerAI/My-Name-is-Riemann-Prerelease-basic-demo) (article completion, token-level surprisal, fluency test). See also the [OpenPeerLLM Demo](https://huggingface.co/spaces/OpenPeerAI/OpenPeerLLM-Demo), which puts the 13.1B Prerelease next to its 163M starting rung, and the [NTK Trainer Demo](https://huggingface.co/spaces/OpenPeerAI/NTK-Trainer-Demo), which fits a gate controller on this model live.
 ## Uses