Instructions to use SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0
# Run inference directly in the terminal:
llama cli -hf SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0
# Run inference directly in the terminal:
llama cli -hf SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0

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 SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0

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 SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0

Use Docker

docker model run hf.co/SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0

LM Studio
Jan
Ollama
How to use SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM with Ollama:
```
ollama run hf.co/SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0
```
Unsloth Desktop
Docker Model Runner
How to use SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM with Docker Model Runner:
```
docker model run hf.co/SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0
```

Lemonade

How to use SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored_ARM:Q4_0

Run and chat with the model

lemonade run user.Phi-3.5-mini-instruct_Uncensored_ARM-Q4_0

List all available models

lemonade list

Atomic Chat

Phi-3.5-mini-instruct_Uncensored_ARM / Phi-3.5-mini-instruct_Uncensored-q4_0_8_8.gguf

SicariusSicariiStuff

Upload 3 files

56ea558 verified almost 2 years ago

Download

History Blame GGUF Editor new Delete

2.18 GB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: b7c2339213ae1149caa5ec01e70d8b46c9ae434a64468dad0ac7d67d4bf7d00b
Size of remote file:: 2.18 GB
SHA256:: ac4f6798423936e8c59c9f00d76e3c57933e16a3316a28a7630052bda952e4e7

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.