Instructions to use michsethowusu/Akiti-TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use michsethowusu/Akiti-TTS with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="michsethowusu/Akiti-TTS",
	filename="VieNeu-TTS-Twi-Q4_K_M.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 michsethowusu/Akiti-TTS with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf michsethowusu/Akiti-TTS:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf michsethowusu/Akiti-TTS:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf michsethowusu/Akiti-TTS:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf michsethowusu/Akiti-TTS: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 michsethowusu/Akiti-TTS:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf michsethowusu/Akiti-TTS: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 michsethowusu/Akiti-TTS:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf michsethowusu/Akiti-TTS:Q4_K_M

Use Docker

docker model run hf.co/michsethowusu/Akiti-TTS:Q4_K_M

LM Studio
Jan
Ollama
How to use michsethowusu/Akiti-TTS with Ollama:
```
ollama run hf.co/michsethowusu/Akiti-TTS:Q4_K_M
```

Unsloth Studio

How to use michsethowusu/Akiti-TTS 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 michsethowusu/Akiti-TTS 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 michsethowusu/Akiti-TTS to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for michsethowusu/Akiti-TTS to start chatting

Docker Model Runner
How to use michsethowusu/Akiti-TTS with Docker Model Runner:
```
docker model run hf.co/michsethowusu/Akiti-TTS:Q4_K_M
```

Lemonade

How to use michsethowusu/Akiti-TTS with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull michsethowusu/Akiti-TTS:Q4_K_M

Run and chat with the model

lemonade run user.Akiti-TTS-Q4_K_M

List all available models

lemonade list

michsethowusu commited on 5 days ago

Commit

09bc0ab

verified ·

1 Parent(s): 9df90d8

usage stats

Browse files

Files changed (1) hide show

usage/1780489256_242f7e2f.json +16 -0

usage/1780489256_242f7e2f.json ADDED Viewed

	@@ -0,0 +1,16 @@

+{
+  "threads": 6,
+  "rtf": 1.83,
+  "model": "q8",
+  "cpu_count": 6,
+  "audio_seconds": 6.66,
+  "load_seconds": 9.24,
+  "arch": "x86_64",
+  "gen_seconds": 12.17,
+  "script_version": "1.0.0-web",
+  "os": "Linux",
+  "speech_codes": 334,
+  "cpu": "x86_64",
+  "python": "3.10.12",
+  "server_ts": 1780489256
+}