Instructions to use Aryanne/MixSwap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aryanne/MixSwap with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Aryanne/MixSwap")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Aryanne/MixSwap") model = AutoModelForCausalLM.from_pretrained("Aryanne/MixSwap") - llama-cpp-python
How to use Aryanne/MixSwap with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Aryanne/MixSwap", filename="f16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Aryanne/MixSwap with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Aryanne/MixSwap:F16 # Run inference directly in the terminal: llama-cli -hf Aryanne/MixSwap:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Aryanne/MixSwap:F16 # Run inference directly in the terminal: llama-cli -hf Aryanne/MixSwap:F16
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Aryanne/MixSwap:F16 # Run inference directly in the terminal: ./llama-cli -hf Aryanne/MixSwap:F16
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Aryanne/MixSwap:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Aryanne/MixSwap:F16
Use Docker
docker model run hf.co/Aryanne/MixSwap:F16
- LM Studio
- Jan
- vLLM
How to use Aryanne/MixSwap with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Aryanne/MixSwap" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Aryanne/MixSwap", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Aryanne/MixSwap:F16
- SGLang
How to use Aryanne/MixSwap 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 "Aryanne/MixSwap" \ --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": "Aryanne/MixSwap", "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 "Aryanne/MixSwap" \ --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": "Aryanne/MixSwap", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use Aryanne/MixSwap with Ollama:
ollama run hf.co/Aryanne/MixSwap:F16
- Unsloth Studio new
How to use Aryanne/MixSwap with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Aryanne/MixSwap to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Aryanne/MixSwap to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Aryanne/MixSwap to start chatting
- Docker Model Runner
How to use Aryanne/MixSwap with Docker Model Runner:
docker model run hf.co/Aryanne/MixSwap:F16
- Lemonade
How to use Aryanne/MixSwap with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Aryanne/MixSwap:F16
Run and chat with the model
lemonade run user.MixSwap-F16
List all available models
lemonade list
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Aryanne/MixSwap")
model = AutoModelForCausalLM.from_pretrained("Aryanne/MixSwap")MixSwap
This is a merge of pre-trained language models created using mergekit, but my branch was used here
Merge Details
Merge Method
This model was merged using the task_swapping merge method using Aryanne/Open-StarLake-Swap-7B as a base.
Models Merged
The following models were included in the merge:
- cognitivecomputations/dolphin-2.2.1-mistral-7b
- teknium/Mistral-Trismegistus-7B
- l3utterfly/mistral-7b-v0.1-layla-v4-chatml
Prompt Format:
I prefer using this way, which seems to work.
Example using Koboldcpp:
Start Seq.:
\nYour_name:
End Seq.:
\nCharacter_name:
In Memory
### Instruction:
Character description.
Generate a endless verbose(very descriptive) role-play conversation with Character_name.
### Response:
Your_name: how are you doing babe? *Your_name approaches Character_name and kisses her in the lips*
Character_name: I'm fine, it's been an weird day. *Character_name blushes and hugs Your_name with love*
Configuration
The following YAML configuration was used to produce this model:
base_model:
model:
path: Aryanne/Open-StarLake-Swap-7B
dtype: bfloat16
merge_method: task_swapping
slices:
- sources:
- layer_range: [0, 32]
model:
model:
path: l3utterfly/mistral-7b-v0.1-layla-v4-chatml
parameters:
diagonal_offset: 4.0
random_mask: 0.1
random_mask_seed: 1956557.0
weight: 0.4
- layer_range: [0, 32]
model:
model:
path: cognitivecomputations/dolphin-2.2.1-mistral-7b
parameters:
diagonal_offset: 4.0
random_mask: 0.1
random_mask_seed: 18019.0
weight: 0.333
- layer_range: [0, 32]
model:
model:
path: teknium/Mistral-Trismegistus-7B
parameters:
diagonal_offset: 4.0
random_mask: 0.05
random_mask_seed: 666666.0
weight: 0.5
- layer_range: [0, 32]
model:
model:
path: Aryanne/Open-StarLake-Swap-7B
- Downloads last month
- 148
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Aryanne/MixSwap")