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
| import { describe, expect, it } from 'vitest'; | |
| import { | |
| RECOMMENDED_MCP_SERVER_IDS, | |
| RECOMMENDED_MCP_SERVERS | |
| } from '$lib/constants/recommended-mcp-servers'; | |
| import { parseMcpServerSettings } from '$lib/utils/mcp'; | |
| import { DEFAULT_MCP_CONFIG, MCP_SERVER_ID_PREFIX } from '$lib/constants/mcp'; | |
| /** | |
| * Tests for the predefined recommended MCP servers. | |
| * | |
| * These are surfaced to first-time users via | |
| * DialogMcpServerRecommendations and used as the default value of the MCP | |
| * servers setting, so a regression that breaks the round-trip through the | |
| * settings parser would silently break onboarding for new users. | |
| */ | |
| describe('RECOMMENDED_MCP_SERVERS', () => { | |
| it('lists at least one entry and uses stable, unique ids', () => { | |
| expect(RECOMMENDED_MCP_SERVERS.length).toBeGreaterThan(0); | |
| const ids = RECOMMENDED_MCP_SERVERS.map((server) => server.id); | |
| expect(new Set(ids).size).toBe(ids.length); | |
| for (const id of ids) { | |
| expect(id).toMatch(/^[a-z0-9-]+$/); | |
| expect(id.toLowerCase()).not.toContain(MCP_SERVER_ID_PREFIX.toLowerCase()); | |
| } | |
| }); | |
| it('requires a name, description and url for every entry', () => { | |
| for (const server of RECOMMENDED_MCP_SERVERS) { | |
| expect(server.name?.trim().length ?? 0).toBeGreaterThan(0); | |
| expect(server.description.trim().length).toBeGreaterThan(0); | |
| expect(server.url.trim().length).toBeGreaterThan(0); | |
| expect(() => new URL(server.url)).not.toThrow(); | |
| } | |
| }); | |
| }); | |
| describe('RECOMMENDED_MCP_SERVER_IDS', () => { | |
| it('matches the ids declared in RECOMMENDED_MCP_SERVERS', () => { | |
| expect(RECOMMENDED_MCP_SERVER_IDS.size).toBe(RECOMMENDED_MCP_SERVERS.length); | |
| for (const server of RECOMMENDED_MCP_SERVERS) { | |
| expect(RECOMMENDED_MCP_SERVER_IDS.has(server.id)).toBe(true); | |
| } | |
| }); | |
| }); | |
| describe('recommended-mcp-servers default value', () => { | |
| it('round-trips cleanly through parseMcpServerSettings', () => { | |
| const serialized = JSON.stringify(RECOMMENDED_MCP_SERVERS); | |
| const parsed = parseMcpServerSettings(serialized); | |
| expect(parsed).toHaveLength(RECOMMENDED_MCP_SERVERS.length); | |
| for (let index = 0; index < RECOMMENDED_MCP_SERVERS.length; index++) { | |
| const source = RECOMMENDED_MCP_SERVERS[index]; | |
| const entry = parsed[index]; | |
| expect(entry).toBeDefined(); | |
| expect(entry?.id).toBe(source.id); | |
| expect(entry?.url).toBe(source.url); | |
| expect(entry?.enabled).toBe(source.enabled); | |
| expect(entry?.requestTimeoutSeconds).toBe(source.requestTimeoutSeconds); | |
| expect(entry?.name).toBe(source.name); | |
| // Headers and useProxy are not set on recommended servers; the | |
| // parser must fall back to the inactive defaults rather than | |
| // surfacing undefined-boundary states. | |
| expect(entry?.headers).toBeUndefined(); | |
| expect(entry?.useProxy).toBe(false); | |
| } | |
| }); | |
| it('uses the global default timeout when one is not specified on an entry', () => { | |
| const sourceOnlyRequired = { | |
| id: 'roundtrip-only', | |
| name: 'Only required fields', | |
| url: 'https://example.test/mcp', | |
| description: 'Smoke entry for parser roundtrip with default timeout.', | |
| enabled: true | |
| }; | |
| const parsed = parseMcpServerSettings(JSON.stringify([sourceOnlyRequired])); | |
| const entry = parsed[0]; | |
| expect(entry?.requestTimeoutSeconds).toBe(DEFAULT_MCP_CONFIG.requestTimeoutSeconds); | |
| }); | |
| }); | |