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
| # MIT license | |
| # Copyright (C) 2024 Intel Corporation | |
| # SPDX-License-Identifier: MIT | |
| Help() { | |
| cat << EOF | |
| Usage: $(basename "$0") [OPTIONS] | |
| This script processes files with specified options. | |
| Options: | |
| -h, --help Display this help message and exit. | |
| -c, --context <value> Set context length. Bigger need more memory. | |
| -p, --promote <value> Prompt to start generation with. | |
| -m, --model <value> Full model file path. | |
| -mg,--main-gpu <value> Set main GPU ID (0 - n) for single GPU mode. | |
| -sm,--split-mode <value> How to split the model across multiple GPUs, one of: | |
| - none: use one GPU only | |
| - layer (default): split layers and KV across GPUs | |
| - row: split rows across GPUs | |
| -ngl,--n-gpu-layers <value> Max. number of layers to store in VRAM (default: -1) | |
| -lv,--log-verbosity <value> Set the verbosity threshold. Messages with a higher verbosity will be | |
| ignored. Values: | |
| - 0: generic output | |
| - 1: error | |
| - 2: warning | |
| - 3: info | |
| - 4: debug | |
| EOF | |
| } | |
| BIN_FILE=./build/bin/llama-server | |
| SEED=0 | |
| GPUS_SETTING="" | |
| MODEL_FILE=../models/Qwen3.5-4B-Q4_0.gguf | |
| NGL=99 | |
| CONTEXT=4096 | |
| GGML_SYCL_DEVICE=-1 | |
| SPLIT_MODE=layer | |
| LOG_VERBOSE=3 | |
| while [[ $# -gt 0 ]]; do | |
| case "$1" in | |
| -c|--context) | |
| CONTEXT=$2 | |
| # Shift twice to consume both the option flag and its value | |
| shift | |
| shift | |
| ;; | |
| -m|--model) | |
| MODEL_FILE="$2" | |
| # Shift twice to consume both the option flag and its value | |
| shift | |
| shift | |
| ;; | |
| -mg|--main-gpu) | |
| GGML_SYCL_DEVICE=$2 | |
| SPLIT_MODE=none | |
| # Shift twice to consume both the option flag and its value | |
| shift | |
| shift | |
| ;; | |
| -sm|--split-mode) | |
| SPLIT_MODE=$2 | |
| # Shift twice to consume both the option flag and its value | |
| shift | |
| shift | |
| ;; | |
| -ngl|--n-gpu-layers) | |
| NGL=$2 | |
| # Shift twice to consume both the option flag and its value | |
| shift | |
| shift | |
| ;; | |
| -lv|--log-verbosity) | |
| LOG_VERBOSE=$2 | |
| # Shift twice to consume both the option flag and its value | |
| shift | |
| shift | |
| ;; | |
| -h|--help) | |
| Help | |
| exit 0 | |
| ;; | |
| *) | |
| # Handle unknown options or stop processing options | |
| echo "Invalid option: $1" | |
| # Optional: exit script or shift to treat remaining as positional args | |
| exit 1 | |
| ;; | |
| esac | |
| done | |
| source /opt/intel/oneapi/setvars.sh | |
| #export GGML_SYCL_DEBUG=1 | |
| #ZES_ENABLE_SYSMAN=1, Support to get free memory of GPU by sycl::aspect::ext_intel_free_memory. Recommended to use when --split-mode = layer. | |
| #support malloc device memory more than 4GB. | |
| export UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=1 | |
| echo "UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=${UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS}" | |
| if [ $GGML_SYCL_DEVICE -ne -1 ]; then | |
| echo "Use $GGML_SYCL_DEVICE as main GPU" | |
| #use signle GPU only | |
| GPUS_SETTING="-mg $GGML_SYCL_DEVICE -sm ${SPLIT_MODE}" | |
| echo "ONEAPI_DEVICE_SELECTOR=${ONEAPI_DEVICE_SELECTOR}" | |
| else | |
| echo "Use all Intel GPUs, including iGPU & dGPU" | |
| GPUS_SETTING="-sm ${SPLIT_MODE}" | |
| fi | |
| echo "run cmd: ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --mmap --host 0.0.0.0 --port 8000" | |
| ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --mmap --host 0.0.0.0 --port 8000 | |