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, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

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
```

StripedHyena-Nous-7B / config.json

Zymrael

fix: key in config to match fa flag

d8a5c9f verified over 2 years ago

Raw

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1.68 kB

	{
	"_commit_hash": "9ae63354fd42cc1e14334bba246276540c8b9017",
	"_name_or_path": "togethercomputer/StripedHyena-Nous-7B",
	"model_type": "stripedhyena",
	"architectures": [
	"StripedHyenaModelForCausalLM"
	],
	"attn_layer_idxs": [
	1,
	3,
	5,
	7,
	9,
	11,
	13,
	15,
	17,
	19,
	21,
	23,
	25,
	27,
	29,
	31
	],
	"auto_map": {
	"AutoConfig": "togethercomputer/StripedHyena-Nous-7B--configuration_hyena.StripedHyenaConfig",
	"AutoModelForCausalLM": "togethercomputer/StripedHyena-Nous-7B--modeling_hyena.StripedHyenaModelForCausalLM"
	},
	"column_split": false,
	"column_split_hyena": true,
	"eps": 1e-05,
	"final_norm": true,
	"hidden_size": 4096,
	"hyena_filter_groups": 1,
	"hyena_layer_idxs": [
	0,
	2,
	4,
	6,
	8,
	10,
	12,
	14,
	16,
	18,
	20,
	22,
	24,
	26,
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	],
	"inference_mode": false,
	"inner_mlp_size": 14336,
	"log_intermediate_values": false,
	"make_vocab_size_divisible_by": 8,
	"max_seqlen": 32768,
	"mha_out_proj_bias": false,
	"model_parallel_size": 1,
	"num_attention_heads": 32,
	"num_filters": 4096,
	"num_layers": 32,
	"pipe_parallel_size": 1,
	"prefill_style": "fft",
	"proj_groups": 4,
	"qkv_proj_bias": false,
	"rotary_emb_base": 500000,
	"short_filter_bias": true,
	"short_filter_length": 3,
	"smeared_gqa": false,
	"split_k0": true,
	"state_size": 2,
	"tie_embeddings": false,
	"torch_dtype": "bfloat16",
	"transformers_version": null,
	"use_cache": true,
	"use_flash_attn": true,
	"use_flash_depthwise": false,
	"use_flash_rmsnorm": true,
	"use_flashfft": false,
	"vocab_size": 32000
	}