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
| {%- macro render_content(msg) -%} | |
| {%- set c = msg.get('content') -%} | |
| {%- if c is string -%} | |
| {{ c }} | |
| {%- elif c is not none -%} | |
| {% for content in c -%} | |
| {% if content['type'] == 'image' or 'image' in content or 'image_url' in content -%} | |
| <|media_start|>image<|media_content|><|media_pad|><|media_end|> | |
| {% else -%} | |
| {{ content['text'] }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {% macro set_roles(message) -%} | |
| {%- set role_name = message.get('name') or message['role'] -%} | |
| {%- if message['role'] == 'user' -%} | |
| <|im_user|>{{role_name}}<|im_middle|> | |
| {%- elif message['role'] == 'assistant' -%} | |
| <|im_assistant|>{{role_name}}<|im_middle|> | |
| {%- else -%} | |
| <|im_system|>{{role_name}}<|im_middle|> | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {%- set tool_response_queue = namespace(ids=[]) -%} | |
| {%- set tool_call_counter = namespace(value=0) -%} | |
| {%- macro render_toolcalls(message) -%} | |
| <|tool_calls_section_begin|> | |
| {%- for tool_call in message['tool_calls'] -%} | |
| {%- set formatted_id = 'functions.' + tool_call['function']['name'] + ':' + (tool_call_counter.value | string) -%} | |
| {%- set tool_call_counter.value = tool_call_counter.value + 1 -%} | |
| {%- set _ = tool_response_queue.ids.append(formatted_id) -%} | |
| <|tool_call_begin|>{{ formatted_id }}<|tool_call_argument_begin|>{% if tool_call['function']['arguments'] is string %}{{ tool_call['function']['arguments'] }}{% else %}{{ tool_call['function']['arguments'] | tojson }}{% endif %}<|tool_call_end|> | |
| {%- endfor -%} | |
| <|tool_calls_section_end|> | |
| {%- endmacro -%} | |
| {# Find last non-tool-call assisitant message #} | |
| {%- set ns = namespace(last_non_tool_call_assistant_msg=-1) -%} | |
| {%- for idx in range(messages|length-1, -1, -1) -%} | |
| {%- if messages[idx]['role'] == 'assistant' and not messages[idx].get('tool_calls') -%} | |
| {%- set ns.last_non_tool_call_assistant_msg = idx -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {# split all messages into history & suffix, reasoning_content in suffix should be reserved.#} | |
| {%- set hist_msgs = messages[:ns.last_non_tool_call_assistant_msg+1] -%} | |
| {%- set suffix_msgs = messages[ns.last_non_tool_call_assistant_msg+1:] -%} | |
| {%- if tools -%} | |
| <|im_system|>tool_declare<|im_middle|>{{ tools | tojson }}<|im_end|> | |
| {%- endif -%} | |
| {%- if messages|length == 0 or messages[0]['role'] != 'system' -%} | |
| <|im_system|>system<|im_middle|>You are Kimi, an AI assistant created by Moonshot AI.<|im_end|> | |
| {%- endif -%} | |
| {%- for message in hist_msgs -%} | |
| {{set_roles(message)}} | |
| {%- if message['role'] == 'assistant' -%} | |
| <think></think>{{render_content(message)}} | |
| {%- if message.get('tool_calls') -%} | |
| {{render_toolcalls(message)}} | |
| {%- endif -%} | |
| {%- elif message['role'] == 'tool' -%} | |
| {%- if tool_response_queue.ids -%} | |
| {%- set tool_call_id = tool_response_queue.ids.pop(0) -%} | |
| {%- else -%} | |
| {%- set tool_call_id = 'functions.' + message.get('name', 'unknown') + ':' + (tool_call_counter.value | string) -%} | |
| {%- endif -%} | |
| ## Return of {{ tool_call_id }} | |
| {{render_content(message)}} | |
| {%- elif message['content'] is not none -%} | |
| {{render_content(message)}} | |
| {%- endif -%} | |
| <|im_end|> | |
| {%- endfor -%} | |
| {%- for message in suffix_msgs -%} | |
| {{set_roles(message)}} | |
| {%- if message['role'] == 'assistant' -%} | |
| {%- set rc = message.get('reasoning_content', '') -%} | |
| <think>{{rc}}</think>{{render_content(message)}} | |
| {%- if message.get('tool_calls') -%} | |
| {{render_toolcalls(message)}} | |
| {%- endif -%} | |
| {%- elif message['role'] == 'tool' -%} | |
| {%- if tool_response_queue.ids -%} | |
| {%- set tool_call_id = tool_response_queue.ids.pop(0) -%} | |
| {%- else -%} | |
| {%- set tool_call_id = 'functions.' + message.get('name', 'unknown') + ':' + (tool_call_counter.value | string) -%} | |
| {%- endif -%} | |
| ## Return of {{ tool_call_id }} | |
| {{render_content(message)}} | |
| {%- elif message['content'] is not none -%} | |
| {{render_content(message)}} | |
| {%- endif -%} | |
| <|im_end|> | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| <|im_assistant|>assistant<|im_middle|> | |
| {%- endif -%} | |