Safetensors
GGUF
Turkish
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
Instructions to use tda45/TdAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use tda45/TdAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tda45/TdAI", filename="llama.cpp/models/ggml-vocab-aquila.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 tda45/TdAI 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 tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./llama-cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf tda45/TdAI
Use Docker
docker model run hf.co/tda45/TdAI
- LM Studio
- Jan
- Ollama
How to use tda45/TdAI with Ollama:
ollama run hf.co/tda45/TdAI
- Unsloth Studio
How to use tda45/TdAI 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 tda45/TdAI 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 tda45/TdAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tda45/TdAI to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tda45/TdAI with Docker Model Runner:
docker model run hf.co/tda45/TdAI
- Lemonade
How to use tda45/TdAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tda45/TdAI
Run and chat with the model
lemonade run user.TdAI-{{QUANT_TAG}}List all available models
lemonade list
| set -e | |
| # Read the first argument into a variable | |
| arg1="$1" | |
| # Shift the arguments to remove the first one | |
| shift | |
| if [[ "$arg1" == '--convert' || "$arg1" == '-c' ]]; then | |
| exec python3 ./convert_hf_to_gguf.py "$@" | |
| elif [[ "$arg1" == '--quantize' || "$arg1" == '-q' ]]; then | |
| exec ./llama-quantize "$@" | |
| elif [[ "$arg1" == '--run' || "$arg1" == '-r' ]]; then | |
| exec ./llama-cli "$@" | |
| elif [[ "$arg1" == '--run-legacy' || "$arg1" == '-l' ]]; then | |
| exec ./llama-completion "$@" | |
| elif [[ "$arg1" == '--bench' || "$arg1" == '-b' ]]; then | |
| exec ./llama-bench "$@" | |
| elif [[ "$arg1" == '--perplexity' || "$arg1" == '-p' ]]; then | |
| exec ./llama-perplexity "$@" | |
| elif [[ "$arg1" == '--all-in-one' || "$arg1" == '-a' ]]; then | |
| echo "Converting PTH to GGML..." | |
| for i in $(ls $1/$2/ggml-model-f16.bin*); do | |
| if [ -f "${i/f16/q4_0}" ]; then | |
| echo "Skip model quantization, it already exists: ${i/f16/q4_0}" | |
| else | |
| echo "Converting PTH to GGML: $i into ${i/f16/q4_0}..." | |
| exec ./llama-quantize "$i" "${i/f16/q4_0}" q4_0 | |
| fi | |
| done | |
| elif [[ "$arg1" == '--server' || "$arg1" == '-s' ]]; then | |
| exec ./llama-server "$@" | |
| else | |
| echo "Unknown command: $arg1" | |
| echo "Available commands: " | |
| echo " --run (-r): Run a model (chat) previously converted into ggml" | |
| echo " ex: -m /models/7B/ggml-model-q4_0.bin" | |
| echo " --run-legacy (-l): Run a model (legacy completion) previously converted into ggml" | |
| echo " ex: -m /models/7B/ggml-model-q4_0.bin -no-cnv -p \"Building a website can be done in 10 simple steps:\" -n 512" | |
| echo " --bench (-b): Benchmark the performance of the inference for various parameters." | |
| echo " ex: -m model.gguf" | |
| echo " --perplexity (-p): Measure the perplexity of a model over a given text." | |
| echo " ex: -m model.gguf -f file.txt" | |
| echo " --convert (-c): Convert a llama model into ggml" | |
| echo " ex: --outtype f16 \"/models/7B/\" " | |
| echo " --quantize (-q): Optimize with quantization process ggml" | |
| echo " ex: \"/models/7B/ggml-model-f16.bin\" \"/models/7B/ggml-model-q4_0.bin\" 2" | |
| echo " --all-in-one (-a): Execute --convert & --quantize" | |
| echo " ex: \"/models/\" 7B" | |
| echo " --server (-s): Run a model on the server" | |
| echo " ex: -m /models/7B/ggml-model-q4_0.bin -c 2048 -ngl 43 -mg 1 --port 8080" | |
| fi | |