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.
- 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
File size: 3,991 Bytes
8efb28e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | #!/usr/bin/env python
import pytest
# ensure grandparent path is in sys.path
from pathlib import Path
import sys
from unit.test_tool_call import TEST_TOOL
path = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(path))
import datetime
from utils import *
from typing import Literal
server: ServerProcess
@pytest.fixture(autouse=True)
def create_server():
global server
server = ServerPreset.tinyllama2()
server.model_alias = "tinyllama-2"
server.n_slots = 1
@pytest.mark.parametrize("tools", [None, [], [TEST_TOOL]])
@pytest.mark.parametrize("template_name,reasoning,expected_end", [
("deepseek-ai-DeepSeek-R1-Distill-Qwen-32B", "on", "<think>\n"),
("deepseek-ai-DeepSeek-R1-Distill-Qwen-32B","auto", "<think>\n"),
("deepseek-ai-DeepSeek-R1-Distill-Qwen-32B", "off", "<think>\n</think>"),
("Qwen-Qwen3-0.6B","auto", "<|im_start|>assistant\n"),
("Qwen-Qwen3-0.6B", "off", "<|im_start|>assistant\n<think>\n\n</think>\n\n"),
("Qwen-QwQ-32B","auto", "<|im_start|>assistant\n<think>\n"),
("Qwen-QwQ-32B", "off", "<|im_start|>assistant\n<think>\n</think>"),
("CohereForAI-c4ai-command-r7b-12-2024-tool_use","auto", "<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"),
("CohereForAI-c4ai-command-r7b-12-2024-tool_use", "off", "<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_THINKING|><|END_THINKING|>"),
])
def test_reasoning(template_name: str, reasoning: Literal['on', 'off', 'auto'] | None, expected_end: str, tools: list[dict]):
global server
server.jinja = True
server.reasoning = reasoning
server.chat_template_file = f'../../../models/templates/{template_name}.jinja'
server.start()
res = server.make_request("POST", "/apply-template", data={
"messages": [
{"role": "user", "content": "What is today?"},
],
"tools": tools,
})
assert res.status_code == 200
prompt = res.body["prompt"]
assert prompt.endswith(expected_end), f"Expected prompt to end with '{expected_end}', got '{prompt}'"
@pytest.mark.parametrize("tools", [None, [], [TEST_TOOL]])
@pytest.mark.parametrize("template_name,format", [
("meta-llama-Llama-3.3-70B-Instruct", "%d %b %Y"),
("fireworks-ai-llama-3-firefunction-v2", "%b %d %Y"),
])
def test_date_inside_prompt(template_name: str, format: str, tools: list[dict]):
global server
server.jinja = True
server.chat_template_file = f'../../../models/templates/{template_name}.jinja'
server.start()
res = server.make_request("POST", "/apply-template", data={
"messages": [
{"role": "user", "content": "What is today?"},
],
"tools": tools,
})
assert res.status_code == 200
prompt = res.body["prompt"]
today_str = datetime.date.today().strftime(format)
assert today_str in prompt, f"Expected today's date ({today_str}) in content ({prompt})"
@pytest.mark.parametrize("add_generation_prompt", [False, True])
@pytest.mark.parametrize("template_name,expected_generation_prompt", [
("meta-llama-Llama-3.3-70B-Instruct", "<|start_header_id|>assistant<|end_header_id|>"),
])
def test_add_generation_prompt(template_name: str, expected_generation_prompt: str, add_generation_prompt: bool):
global server
server.jinja = True
server.chat_template_file = f'../../../models/templates/{template_name}.jinja'
server.start()
res = server.make_request("POST", "/apply-template", data={
"messages": [
{"role": "user", "content": "What is today?"},
],
"add_generation_prompt": add_generation_prompt,
})
assert res.status_code == 200
prompt = res.body["prompt"]
if add_generation_prompt:
assert expected_generation_prompt in prompt, f"Expected generation prompt ({expected_generation_prompt}) in content ({prompt})"
else:
assert expected_generation_prompt not in prompt, f"Did not expect generation prompt ({expected_generation_prompt}) in content ({prompt})"
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