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
| /** | |
| * Detects whether a model's chat template supports thinking/reasoning control. | |
| * | |
| * The server "/props" endpoint does NOT expose a supports_thinking flag. | |
| * It is computed internally by common_chat_templates_support_enable_thinking | |
| * in common/chat.cpp. A proper server flag would make this unnecessary. | |
| * | |
| * Detection order (most reliable first): | |
| * 1. Thinking-control Jinja2 variables === pass-through via chat_template_kwargs | |
| * 2. Thinking-control Jinja2 conditionals === template-native on/off logic | |
| * 3. Paired thinking-content tag pairs === models that output special tags | |
| */ | |
| const THINKING_KWARG_VARS = ['enable_thinking', 'reasoning_effort', 'thinking_budget']; | |
| /** | |
| * Paired thinking-content tag patterns. | |
| * | |
| * Inspected: llama-cpp-deepseek-r1/v3, nim-nemotron-{3,4}-nano, qwen-qwq-32b, | |
| * qwen-3-32b, google-gemma-4-31b-it, kimikimi-k2-thinking, apertus-8b-instruct, | |
| * mistralai-Mistral-Small-3.2-24B, ByteDance-Seed-OSS. | |
| * | |
| * The self-closing entry is Kimi-K2, Gemma4 fixed-length pair, | |
| * where both tags always appear adjacent with no content between. | |
| */ | |
| const THINKING_TAG_PATTERNS: Array<[string, string | null]> = [ | |
| ['<think>', '</think>'], | |
| ['<|channel>thought', '<|channel|>'], | |
| ['<|think|>', '</|think|>'], | |
| ['<seed:think|>', '</seed:think|>'], | |
| ['<think></think>', null] | |
| ]; | |
| const JINJA_THINKING_CONDITIONALS: RegExp[] = [ | |
| // Matches: {% if enable thinking %}, {% if enable_thinking %}, {% if (enable_thinking is defined) %} | |
| // Handles: underscore-separated (enable_thinking), space-separated (enable thinking), | |
| // and optional parens/brackets before enable (if (enable_thinking ) | |
| /\{%-?\s*if\s+\(?\s*\w*enable[\s_]+\w*(thinking|think|reasoning)/i, | |
| /\{%-?\s*if\s+\w*(thinking|reasoning)\s*(is not|==|!=)/i, | |
| /\{%-?\s*if\s+not\s+\w*enable/i, | |
| /\{%-?\s*if\s+ns\.enable_thinking/i | |
| ]; | |
| /** Guards against false positives: | |
| * - Generic thought keyword (tool descriptions say "chain of thought") | |
| * - Qwen vertical-bar token (used for ALL tool calls, not thinking) | |
| */ | |
| export function detectThinkingSupport(t: string): boolean { | |
| if (!t) return false; | |
| for (const kwarg of THINKING_KWARG_VARS) { | |
| const regex = new RegExp( | |
| `(\\{\\{[^{}]*\\b${kwarg}\\b[^{}]*\\}\\}|\\{%[^{}]*\\b${kwarg}\\b[^{}]*%\\})`, | |
| 'i' | |
| ); | |
| if (regex.test(t)) return true; | |
| } | |
| for (const p of JINJA_THINKING_CONDITIONALS) { | |
| if (p.test(t)) return true; | |
| } | |
| for (const [s, e] of THINKING_TAG_PATTERNS) { | |
| if (t.includes(s) && (!e || t.includes(e))) return true; | |
| } | |
| return false; | |
| } | |
| export function detectThinkingSupportWithReason(t: string): { supported: boolean; reason: string } { | |
| if (!t) return { supported: false, reason: 'No chat template available' }; | |
| for (const kwarg of THINKING_KWARG_VARS) { | |
| const regex = new RegExp( | |
| `(\\{\\{[^{}]*\\b${kwarg}\\b[^{}]*\\}\\}|\\{%[^{}]*\\b${kwarg}\\b[^{}]*%\\})`, | |
| 'i' | |
| ); | |
| if (regex.test(t)) { | |
| return { supported: true, reason: 'Found: ' + kwarg }; | |
| } | |
| } | |
| for (const p of JINJA_THINKING_CONDITIONALS) { | |
| if (p.test(t)) return { supported: true, reason: 'Found: thinking conditional' }; | |
| } | |
| for (const [s, e] of THINKING_TAG_PATTERNS) { | |
| if (t.includes(s) && (!e || t.includes(e))) { | |
| return { supported: true, reason: 'Found: ' + s + (e ? ' .. ' + e : ' (self)') }; | |
| } | |
| } | |
| return { supported: false, reason: 'No thinking patterns found' }; | |
| } | |