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
flowchart TB
subgraph Routes["π Routes"]
R1["/ (Welcome)"]
R2["/chat/[id]"]
RL["+layout.svelte"]
end
subgraph Components["π§© Components"]
C_Sidebar["ChatSidebar"]
C_Screen["ChatScreen"]
C_Form["ChatForm"]
C_Messages["ChatMessages"]
C_Message["ChatMessage"]
C_ChatMessageAgenticContent["ChatMessageAgenticContent"]
C_MessageEditForm["ChatMessageEditForm"]
C_ModelsSelector["ModelsSelector"]
C_Settings["ChatSettings"]
C_McpSettings["McpServersSettings"]
C_McpResourceBrowser["McpResourceBrowser"]
C_McpServersSelector["McpServersSelector"]
end
subgraph Hooks["πͺ Hooks"]
H1["useModelChangeValidation"]
H2["useProcessingState"]
end
subgraph Stores["ποΈ Stores"]
S1["chatStore<br/><i>Chat interactions & streaming</i>"]
SA["agenticStore<br/><i>Multi-turn agentic loop orchestration</i>"]
S2["conversationsStore<br/><i>Conversation data, messages & MCP overrides</i>"]
S3["modelsStore<br/><i>Model selection & loading</i>"]
S4["serverStore<br/><i>Server props & role detection</i>"]
S5["settingsStore<br/><i>User configuration incl. MCP</i>"]
S6["mcpStore<br/><i>MCP servers, tools, prompts</i>"]
S7["mcpResourceStore<br/><i>MCP resources & attachments</i>"]
end
subgraph Services["βοΈ Services"]
SV1["ChatService"]
SV2["ModelsService"]
SV3["PropsService"]
SV4["DatabaseService"]
SV5["ParameterSyncService"]
SV6["MCPService<br/><i>protocol operations</i>"]
end
subgraph Storage["πΎ Storage"]
ST1["IndexedDB<br/><i>conversations, messages</i>"]
ST2["LocalStorage<br/><i>config, userOverrides, mcpServers</i>"]
end
subgraph APIs["π llama-server API"]
API1["/v1/chat/completions"]
API2["/props"]
API3["/models/*"]
API4["/v1/models"]
end
subgraph ExternalMCP["π External MCP Servers"]
EXT1["MCP Server 1<br/><i>WebSocket/HTTP/SSE</i>"]
EXT2["MCP Server N"]
end
%% Routes β Components
R1 & R2 --> C_Screen
RL --> C_Sidebar
%% Layout runs MCP health checks
RL --> S6
%% Component hierarchy
C_Screen --> C_Form & C_Messages & C_Settings
C_Messages --> C_Message
C_Message --> C_ChatMessageAgenticContent
C_Message --> C_MessageEditForm
C_Form & C_MessageEditForm --> C_ModelsSelector
C_Form --> C_McpServersSelector
C_Settings --> C_McpSettings
C_McpSettings --> C_McpResourceBrowser
%% Components β Hooks β Stores
C_Form & C_Messages --> H1 & H2
H1 --> S3 & S4
H2 --> S1 & S5
%% Components β Stores
C_Screen --> S1 & S2
C_Sidebar --> S2
C_ModelsSelector --> S3 & S4
C_Settings --> S5
C_McpSettings --> S6
C_McpResourceBrowser --> S6 & S7
C_McpServersSelector --> S6
C_Form --> S6
%% chatStore β agenticStore β mcpStore (agentic loop)
S1 --> SA
SA --> SV1
SA --> S6
%% Stores β Services
S1 --> SV1 & SV4
S2 --> SV4
S3 --> SV2 & SV3
S4 --> SV3
S5 --> SV5
S6 --> SV6
S7 --> SV6
%% Services β Storage
SV4 --> ST1
SV5 --> ST2
%% Services β APIs
SV1 --> API1
SV2 --> API3 & API4
SV3 --> API2
%% MCP β External Servers
SV6 --> EXT1 & EXT2
%% Styling
classDef routeStyle fill:#e1f5fe,stroke:#01579b,stroke-width:2px
classDef componentStyle fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
classDef hookStyle fill:#fff8e1,stroke:#ff8f00,stroke-width:2px
classDef storeStyle fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef serviceStyle fill:#e8f5e9,stroke:#2e7d32,stroke-width:2px
classDef storageStyle fill:#fce4ec,stroke:#c2185b,stroke-width:2px
classDef apiStyle fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
classDef mcpStyle fill:#e0f2f1,stroke:#00695c,stroke-width:2px
classDef agenticStyle fill:#e8eaf6,stroke:#283593,stroke-width:2px
classDef externalStyle fill:#f3e5f5,stroke:#6a1b9a,stroke-width:2px,stroke-dasharray: 5 5
class R1,R2,RL routeStyle
class C_Sidebar,C_Screen,C_Form,C_Messages,C_Message,C_ChatMessageAgenticContent,C_MessageEditForm,C_ModelsSelector,C_Settings componentStyle
class C_McpSettings,C_McpResourceBrowser,C_McpServersSelector componentStyle
class H1,H2 hookStyle
class S1,S2,S3,S4,S5,SA,S6,S7 storeStyle
class SV1,SV2,SV3,SV4,SV5,SV6 serviceStyle
class ST1,ST2 storageStyle
class API1,API2,API3,API4 apiStyle
class EXT1,EXT2 externalStyle