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
| <script lang="ts"> | |
| import { Wrench, Database, MessageSquare, FileText, Sparkles, ListChecks } from '@lucide/svelte'; | |
| import type { MCPCapabilitiesInfo } from '$lib/types'; | |
| import { Badge } from '$lib/components/ui/badge'; | |
| interface Props { | |
| capabilities?: MCPCapabilitiesInfo; | |
| } | |
| let { capabilities }: Props = $props(); | |
| </script> | |
| {#if capabilities} | |
| {#if capabilities.server.tools} | |
| <Badge variant="outline" class="h-5 gap-1 bg-green-50 px-1.5 text-[10px] dark:bg-green-950"> | |
| <Wrench class="h-3 w-3 text-green-600 dark:text-green-400" /> | |
| Tools | |
| </Badge> | |
| {/if} | |
| {#if capabilities.server.resources} | |
| <Badge variant="outline" class="h-5 gap-1 bg-blue-50 px-1.5 text-[10px] dark:bg-blue-950"> | |
| <Database class="h-3 w-3 text-blue-600 dark:text-blue-400" /> | |
| Resources | |
| </Badge> | |
| {/if} | |
| {#if capabilities.server.prompts} | |
| <Badge variant="outline" class="h-5 gap-1 bg-purple-50 px-1.5 text-[10px] dark:bg-purple-950"> | |
| <MessageSquare class="h-3 w-3 text-purple-600 dark:text-purple-400" /> | |
| Prompts | |
| </Badge> | |
| {/if} | |
| {#if capabilities.server.logging} | |
| <Badge variant="outline" class="h-5 gap-1 bg-orange-50 px-1.5 text-[10px] dark:bg-orange-950"> | |
| <FileText class="h-3 w-3 text-orange-600 dark:text-orange-400" /> | |
| Logging | |
| </Badge> | |
| {/if} | |
| {#if capabilities.server.completions} | |
| <Badge variant="outline" class="h-5 gap-1 bg-cyan-50 px-1.5 text-[10px] dark:bg-cyan-950"> | |
| <Sparkles class="h-3 w-3 text-cyan-600 dark:text-cyan-400" /> | |
| Completions | |
| </Badge> | |
| {/if} | |
| {#if capabilities.server.tasks} | |
| <Badge variant="outline" class="h-5 gap-1 bg-pink-50 px-1.5 text-[10px] dark:bg-pink-950"> | |
| <ListChecks class="h-3 w-3 text-pink-600 dark:text-pink-400" /> | |
| Tasks | |
| </Badge> | |
| {/if} | |
| {/if} | |