Instructions to use soendup21/t2s_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use soendup21/t2s_model2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("soendup21/t2s_model2", dtype="auto") - llama-cpp-python
How to use soendup21/t2s_model2 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="soendup21/t2s_model2", filename="unsloth.Q4_K_M.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 soendup21/t2s_model2 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf soendup21/t2s_model2:Q4_K_M # Run inference directly in the terminal: llama-cli -hf soendup21/t2s_model2:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf soendup21/t2s_model2:Q4_K_M # Run inference directly in the terminal: llama-cli -hf soendup21/t2s_model2: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 soendup21/t2s_model2:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf soendup21/t2s_model2: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 soendup21/t2s_model2:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf soendup21/t2s_model2:Q4_K_M
Use Docker
docker model run hf.co/soendup21/t2s_model2:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use soendup21/t2s_model2 with Ollama:
ollama run hf.co/soendup21/t2s_model2:Q4_K_M
- Unsloth Studio new
How to use soendup21/t2s_model2 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 soendup21/t2s_model2 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 soendup21/t2s_model2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for soendup21/t2s_model2 to start chatting
- Docker Model Runner
How to use soendup21/t2s_model2 with Docker Model Runner:
docker model run hf.co/soendup21/t2s_model2:Q4_K_M
- Lemonade
How to use soendup21/t2s_model2 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull soendup21/t2s_model2:Q4_K_M
Run and chat with the model
lemonade run user.t2s_model2-Q4_K_M
List all available models
lemonade list
How to use from
LemonadeRun and chat with the model
lemonade run user.t2s_model2-Q4_K_MList all available models
lemonade listQuick Links
Uploaded model
- Developed by: soendup21
- License: apache-2.0
- Finetuned from model : unsloth/Meta-Llama-3.1-8B-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Hardware compatibility
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4-bit
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Model tree for soendup21/t2s_model2
Base model
meta-llama/Llama-3.1-8B Quantized
unsloth/Meta-Llama-3.1-8B-bnb-4bit
Pull the model
# Download Lemonade from https://lemonade-server.ai/