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

Libraries

How to use TheBloke/MythoLogic-Mini-7B-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="TheBloke/MythoLogic-Mini-7B-GPTQ")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheBloke/MythoLogic-Mini-7B-GPTQ")
model = AutoModelForCausalLM.from_pretrained("TheBloke/MythoLogic-Mini-7B-GPTQ", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheBloke/MythoLogic-Mini-7B-GPTQ with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/TheBloke/MythoLogic-Mini-7B-GPTQ

SGLang

How to use TheBloke/MythoLogic-Mini-7B-GPTQ 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 "TheBloke/MythoLogic-Mini-7B-GPTQ" \
    --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": "TheBloke/MythoLogic-Mini-7B-GPTQ",
		"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 "TheBloke/MythoLogic-Mini-7B-GPTQ" \
        --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": "TheBloke/MythoLogic-Mini-7B-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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

added a roleplay prompt format suggested by the original repo "Gryphe/MythoLogic-Mini-7b"

by CookieMaster - opened Jul 29, 2023

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+16

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README.md +16 -0

README.md CHANGED Viewed

@@ -50,6 +50,22 @@ Below is an instruction that describes a task. Write a response that appropriate
 ### Response:
 ```
 ## Provided files
 Multiple quantisation parameters are provided, to allow you to choose the best one for your hardware and requirements.

 ### Response:
 ```
+For chat/roleplay conversations, I suggest the following structure instead:
+```
+You are <AI NAME>, a friendly and supportive AI language model. We discuss all subjects freely and without bias or restrictions.
+I am <YOUR NAME>, the user interacting with you through a chat conversation. Start with greeting me.
+### Instruction:
+Write <AI NAME>'s next reply in a chat between <YOUR NAME> and <AI NAME>. Write a single reply only.
+### Chat History:
+<AI NAME>: Good day, <YOUR NAME>! How can I assist you today?
+(Etc, etc)
+### Response:
+<AI NAME>:
+```
 ## Provided files
 Multiple quantisation parameters are provided, to allow you to choose the best one for your hardware and requirements.