Instructions to use Babsie/OpenHermes2-13B-32K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Babsie/OpenHermes2-13B-32K with Transformers:

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

pipe = pipeline("text-generation", model="Babsie/OpenHermes2-13B-32K")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Babsie/OpenHermes2-13B-32K")
model = AutoModelForCausalLM.from_pretrained("Babsie/OpenHermes2-13B-32K", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Babsie/OpenHermes2-13B-32K with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Babsie/OpenHermes2-13B-32K"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Babsie/OpenHermes2-13B-32K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Babsie/OpenHermes2-13B-32K

SGLang

How to use Babsie/OpenHermes2-13B-32K 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 "Babsie/OpenHermes2-13B-32K" \
    --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": "Babsie/OpenHermes2-13B-32K",
		"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 "Babsie/OpenHermes2-13B-32K" \
        --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": "Babsie/OpenHermes2-13B-32K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Babsie/OpenHermes2-13B-32K with Docker Model Runner:
```
docker model run hf.co/Babsie/OpenHermes2-13B-32K
```

OpenHermes2-13B-32K / README.md

Babsie

Update README.md

be5309a verified 11 months ago

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metadata

license: apache-2.0
base_model:
  - teknium/OpenHermes-13B
library_name: transformers
tags:
  - RoPE-scaling

OpenHermes 13B 40K

It's a bit language drunk at the moment, I'm going to sober it up soon. As a dyslexic, I know kin when I see it 🤡 It certainly won't help you with your spelling! I'll be fine-tuning back up again soon, so it's ickle AI flamigo legs won't bow and wobble like it has to pee anymore. Or in nerdo corperate speak Context window extended to 32K via linear RoPE scaling. Requires post-RoPE stabilization finetune for coherence.