Instructions to use LongSafari/hyenadna-medium-160k-seqlen-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LongSafari/hyenadna-medium-160k-seqlen-hf with Transformers:

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

pipe = pipeline("text-generation", model="LongSafari/hyenadna-medium-160k-seqlen-hf", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("LongSafari/hyenadna-medium-160k-seqlen-hf", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LongSafari/hyenadna-medium-160k-seqlen-hf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LongSafari/hyenadna-medium-160k-seqlen-hf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LongSafari/hyenadna-medium-160k-seqlen-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LongSafari/hyenadna-medium-160k-seqlen-hf

SGLang

How to use LongSafari/hyenadna-medium-160k-seqlen-hf 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 "LongSafari/hyenadna-medium-160k-seqlen-hf" \
    --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": "LongSafari/hyenadna-medium-160k-seqlen-hf",
		"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 "LongSafari/hyenadna-medium-160k-seqlen-hf" \
        --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": "LongSafari/hyenadna-medium-160k-seqlen-hf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LongSafari/hyenadna-medium-160k-seqlen-hf with Docker Model Runner:
```
docker model run hf.co/LongSafari/hyenadna-medium-160k-seqlen-hf
```

matt commited on Jan 18, 2024

Commit

50b3acf

1 Parent(s): ba3fe0f

Revert change to tokenizer_config too

Browse files

Files changed (1) hide show

tokenizer_config.json +1 -1

tokenizer_config.json CHANGED Viewed

@@ -61,7 +61,7 @@
   "cls_token": "[CLS]",
   "eos_token": "[SEP]",
   "mask_token": "[MASK]",
-  "model_max_length": 1000002,
   "pad_token": "[PAD]",
   "padding_side": "left",
   "sep_token": "[SEP]",

   "cls_token": "[CLS]",
   "eos_token": "[SEP]",
   "mask_token": "[MASK]",
+  "model_max_length": 160002,
   "pad_token": "[PAD]",
   "padding_side": "left",
   "sep_token": "[SEP]",