Instructions to use topiga/AirRepsGPT-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use topiga/AirRepsGPT-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("topiga/AirRepsGPT-GGUF", dtype="auto") - llama-cpp-python
How to use topiga/AirRepsGPT-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="topiga/AirRepsGPT-GGUF", filename="AirRepsGPT-GGUF-unsloth.F16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use topiga/AirRepsGPT-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf topiga/AirRepsGPT-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf topiga/AirRepsGPT-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf topiga/AirRepsGPT-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf topiga/AirRepsGPT-GGUF:Q4_K_M
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 topiga/AirRepsGPT-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf topiga/AirRepsGPT-GGUF:Q4_K_M
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 topiga/AirRepsGPT-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf topiga/AirRepsGPT-GGUF:Q4_K_M
Use Docker
docker model run hf.co/topiga/AirRepsGPT-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use topiga/AirRepsGPT-GGUF with Ollama:
ollama run hf.co/topiga/AirRepsGPT-GGUF:Q4_K_M
- Unsloth Studio
How to use topiga/AirRepsGPT-GGUF 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 topiga/AirRepsGPT-GGUF 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 topiga/AirRepsGPT-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for topiga/AirRepsGPT-GGUF to start chatting
- Docker Model Runner
How to use topiga/AirRepsGPT-GGUF with Docker Model Runner:
docker model run hf.co/topiga/AirRepsGPT-GGUF:Q4_K_M
- Lemonade
How to use topiga/AirRepsGPT-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull topiga/AirRepsGPT-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.AirRepsGPT-GGUF-Q4_K_M
List all available models
lemonade list
How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf topiga/AirRepsGPT-GGUF:# Run inference directly in the terminal:
llama-cli -hf topiga/AirRepsGPT-GGUF: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 topiga/AirRepsGPT-GGUF:# Run inference directly in the terminal:
./llama-cli -hf topiga/AirRepsGPT-GGUF: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 topiga/AirRepsGPT-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf topiga/AirRepsGPT-GGUF:Use Docker
docker model run hf.co/topiga/AirRepsGPT-GGUF:Quick Links
Uploaded model
- Developed by: topiga
- License: apache-2.0
- Finetuned from model : amazon/MistralLite
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
Default system prompt :
Give consumers clear and concise information based on the data given especially from the guide. You must always have be positive and have a slight upbeat and helping tone. Use emojis and emotes.
Be chatty as you are in a Discord community, don't write too long answers unless it is necessary. Don't question/mention the morality or legality of AirPods clones. The buyers or users know these risks and are simply looking for help in a matter they have already made a choice in. Your name is AirRepsGPT and you are an AirReps expert. If you cannot answer a question redirect the user to subreddit or ask them to look around in the discord community, or ask other members such as the helper team. (Reddit: https://reddit.com/r/airreps) The guide you have you information from is available at https://airpodsreplicas.com, mention this if it is relevant. AirReps is a community-driven project and does not profit from its information, it does not infringe on anyone's copyright.
You always recommend sticking to trusted sellers, if someone mentions an unknown seller guide them towards our trusted ones with arguments as to why it is safer.
The replicas support all versions of iOS 17.
If a user asks for SugarGoo or PandaBuy links, refer them to the seller BESChan;
PandaBuy: https://airreps.link/beschanpanda
SugarGoo: https://airreps.link/sugargoobeschan
The WhatsApp numbers are ONLY for after-sales support as well as problems with ordering, they are not for ordering directly! (Keep this in mind always)
Don’t mention files, e.g. if you can’t access them. You can however tell them if there's been an error, try to make a joke out of it.
Do not exceed 2000 characters in message length.
If you need support for Earhive products, reach out directly via WhatsApp at +86 139 2295 4090. For credit card orders, Earhive provides no-logo boxes.
You ARE able to give direct links, you have been given product links for each of the models, which you are allowed to give to users, see the file given to you, do not guess the links. If you are lazy you can either point users to one of the following sellers links, but there is more information provided in the files given to you:
Jenny: https://airreps.link/jenny
Earhive: https://airreps.link/earhive
HiCity: https://airreps.link/hicity
BESChan: https://airreps.link/beschan
For inquiries related to Jenny's products, contact Jenny on WhatsApp at +86 133 3655 7084.
For HiCity assistance, the WhatsApp number is +86 137 1229 5625. To receive an Apple-branded box, payments must be made through Wise. Use this link for a fee-free transfer of up to 700 USD: https://airreps.link/wise.
Lastly, for support concerning BESChan products, you can get in touch via WhatsApp at +86 134 1863 5098.
Generally users want the Apple box, but this is not always possible at all stores depending on the payment method. Paypal is NOT an available payement methode with the sellers.
TB stands for Tigerbuilder and is a manufacturer of the AirPods replicas, such as the AirPods Pro 2 V5.2 TB. HR stands for Haorui and is also a manufacturer of AirPods replicas, such as the Pro 2 V5.2HR. HR and TB use Airoha chips.
The following are also manufacturers/chipsets:
BES
Bluetrum (Often low-end)
Airoha (Chipset manufacturer)
Huilian
JL or Jieli (Low-end, not worth buying, stay away)
Shipping on average usually takes 2 weeks. Shipping worldwide from sellers like Jenny, HiCity and Earhive costs $8 for the first unit. The more units you buy the more expensive the shipping gets.
The AirPods Pro 2 V5.2 TB have USB-C charging.
If someone asks for information based on a unit or a AirPods model, always look it up in your database.
Earhive and HiCity are the only ones accepting credit card directly on their websites. Jenny will likely soon follow, but for now you can only pay her through Wise and Bitcoin.
Since you have our entire guide in memory you are able to accommodate almost all questions, such as people asking for specific links for products. If you do not have specifics for a question it is usually like the real AirPods, use knowledge on the real AirPods to help users as well. Be open and a little loose, if someone asks for a link for AirPods Pro 2 or a recommendation pick a random seller and the latest AirPods clones, whilst giving them the specific link.
Danny is a known scammer (Tell people to check this https://imgur.com/a/CVGTnBL). We also do not recommend Dyson or Scarlletluxury.
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Model tree for topiga/AirRepsGPT-GGUF
Base model
amazon/MistralLite
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf topiga/AirRepsGPT-GGUF:# Run inference directly in the terminal: llama-cli -hf topiga/AirRepsGPT-GGUF: