Instructions to use FluffyKaeloky/Midnight-Miqu-103B-v1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FluffyKaeloky/Midnight-Miqu-103B-v1.5 with Transformers:

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

pipe = pipeline("text-generation", model="FluffyKaeloky/Midnight-Miqu-103B-v1.5")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FluffyKaeloky/Midnight-Miqu-103B-v1.5")
model = AutoModelForCausalLM.from_pretrained("FluffyKaeloky/Midnight-Miqu-103B-v1.5", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FluffyKaeloky/Midnight-Miqu-103B-v1.5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FluffyKaeloky/Midnight-Miqu-103B-v1.5"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FluffyKaeloky/Midnight-Miqu-103B-v1.5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FluffyKaeloky/Midnight-Miqu-103B-v1.5

SGLang

How to use FluffyKaeloky/Midnight-Miqu-103B-v1.5 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 "FluffyKaeloky/Midnight-Miqu-103B-v1.5" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FluffyKaeloky/Midnight-Miqu-103B-v1.5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "FluffyKaeloky/Midnight-Miqu-103B-v1.5" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FluffyKaeloky/Midnight-Miqu-103B-v1.5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FluffyKaeloky/Midnight-Miqu-103B-v1.5 with Docker Model Runner:
```
docker model run hf.co/FluffyKaeloky/Midnight-Miqu-103B-v1.5
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Overview

This is a 103B frankenmerge of sophosympatheia/Midnight-Miqu-70B-v1.5 with itself. Please see that model card for details and usage instructions. This model is based on Miqu so it's capable of 32K context.

Quantizations

GGUF
- GGUF-mradermacher
- GGUF-i1-mradermacher
EXL2

Licence and usage restrictions

152334H/miqu-1-70b-sf was based on a leaked version of one of Mistral's models. All miqu-derived models, including this merge, are only suitable for personal use. Mistral has been cool about it so far, but you should be aware that by downloading this merge you are assuming whatever legal risk is iherent in acquiring and using a model based on leaked weights. This merge comes with no warranties or guarantees of any kind, but you probably already knew that. I am not a lawyer and I do not profess to know what we have gotten ourselves into here. You should consult with a lawyer before using any Hugging Face model beyond private use... but definitely don't use this one for that!

Merge Details

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

sophosympatheia/Midnight-Miqu-70B-v1.5

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: sophosympatheiaMidnight-Miqu-70B-v1.5
        layer_range: [0, 40] # 40
  - sources:
      - model: sophosympatheiaMidnight-Miqu-70B-v1.5
        layer_range: [20, 60] # 40
  - sources:
      - model: sophosympatheiaMidnight-Miqu-70B-v1.5
        layer_range: [40, 80] # 40
merge_method: passthrough
dtype: float16

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Safetensors

Model size

103B params

Tensor type

F16

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Quantizations

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FluffyKaeloky
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Midnight-Miqu-103B-v1.5

Overview

Quantizations

Licence and usage restrictions

Merge Details

Merge Method

Models Merged

Configuration

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