Instructions to use togethercomputer/StripedHyena-Nous-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use togethercomputer/StripedHyena-Nous-7B with Transformers:

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

pipe = pipeline("text-generation", model="togethercomputer/StripedHyena-Nous-7B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("togethercomputer/StripedHyena-Nous-7B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use togethercomputer/StripedHyena-Nous-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "togethercomputer/StripedHyena-Nous-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "togethercomputer/StripedHyena-Nous-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/togethercomputer/StripedHyena-Nous-7B

SGLang

How to use togethercomputer/StripedHyena-Nous-7B 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 "togethercomputer/StripedHyena-Nous-7B" \
    --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": "togethercomputer/StripedHyena-Nous-7B",
		"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 "togethercomputer/StripedHyena-Nous-7B" \
        --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": "togethercomputer/StripedHyena-Nous-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use togethercomputer/StripedHyena-Nous-7B with Docker Model Runner:
```
docker model run hf.co/togethercomputer/StripedHyena-Nous-7B
```

How to Finetune striped hyena for custom dataset in colabT4

by Jaykumaran17 - opened Dec 12, 2023

Discussion

Jaykumaran17

Dec 12, 2023

•

edited Dec 13, 2023

Hi Team,
I would like to know the finetuning code details of Striped Hyena Nous 7b.Unlike Transformers models it extends some architectural changes,so should the code for finetuning and training on custom dataset differs.Can i follow same approach to finetune like Zephyr7b?.Hoping for a reference code or additional clarity on this.Also i face some errors while loading model for inference

Jaykumaran17 changed discussion title from How to Finetune striped hyena for custom dataset to How to Finetune striped hyena for custom dataset in colabT4 Dec 13, 2023

Zymrael

Dec 16, 2023

Take a look at this repo for finetuning code: https://github.com/NousResearch/StripedHyenaTrainer

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