Instructions to use Gryphe/MythoLogic-Mini-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Gryphe/MythoLogic-Mini-7b with Transformers:

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

pipe = pipeline("text-generation", model="Gryphe/MythoLogic-Mini-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Gryphe/MythoLogic-Mini-7b")
model = AutoModelForCausalLM.from_pretrained("Gryphe/MythoLogic-Mini-7b")

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Gryphe/MythoLogic-Mini-7b with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Gryphe/MythoLogic-Mini-7b

SGLang

How to use Gryphe/MythoLogic-Mini-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 "Gryphe/MythoLogic-Mini-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": "Gryphe/MythoLogic-Mini-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 "Gryphe/MythoLogic-Mini-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": "Gryphe/MythoLogic-Mini-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Gryphe/MythoLogic-Mini-7b with Docker Model Runner:
```
docker model run hf.co/Gryphe/MythoLogic-Mini-7b
```

Gryphe commited on Jul 29, 2023

Commit

4fa77a9

1 Parent(s): 759b2ac

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@@ -5,7 +5,7 @@ language:
 ---
 ## Model details
-MythoLogic-Mini-7b can be considered the little brother in my Mytho series of models. ([MythoLogic-13b](https://huggingface.co/Gryphe/MythoLogic-13b), [MythoBoros-13b](https://huggingface.co/Gryphe/MythoBoros-13b))
 Its Llama-2 core is powered by [Nous Hermes-2](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b), which is further augmented by [Stable Beluga](https://huggingface.co/stabilityai/StableBeluga-7B) and a carefully distilled [Kimiko LoRa](https://huggingface.co/nRuaif/Kimiko_7B).

 ---
 ## Model details
+MythoLogic-Mini-7b can be considered the little brother in my Mytho series of models: [MythoLogic-13b](https://huggingface.co/Gryphe/MythoLogic-13b) and [MythoBoros-13b](https://huggingface.co/Gryphe/MythoBoros-13b)).
 Its Llama-2 core is powered by [Nous Hermes-2](https://huggingface.co/NousResearch/Nous-Hermes-llama-2-7b), which is further augmented by [Stable Beluga](https://huggingface.co/stabilityai/StableBeluga-7B) and a carefully distilled [Kimiko LoRa](https://huggingface.co/nRuaif/Kimiko_7B).