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 pytest | |
| from utils import * | |
| # We use a F16 MOE gguf as main model, and q4_0 as draft model | |
| server = ServerPreset.stories15m_moe() | |
| MODEL_DRAFT_FILE_URL = "https://huggingface.co/ggml-org/tiny-llamas/resolve/main/stories15M-q4_0.gguf" | |
| def create_server(): | |
| global server | |
| server = ServerPreset.stories15m_moe() | |
| # set default values | |
| server.model_draft = download_file(MODEL_DRAFT_FILE_URL) | |
| server.draft_min = 4 | |
| server.draft_max = 8 | |
| server.fa = "off" | |
| def fixture_create_server(): | |
| return create_server() | |
| def test_with_and_without_draft(): | |
| global server | |
| server.model_draft = None # disable draft model | |
| server.start() | |
| res = server.make_request("POST", "/completion", data={ | |
| "prompt": "I believe the meaning of life is", | |
| "temperature": 0.0, | |
| "top_k": 1, | |
| "n_predict": 16, | |
| }) | |
| assert res.status_code == 200 | |
| content_no_draft = res.body["content"] | |
| server.stop() | |
| # create new server with draft model | |
| create_server() | |
| server.start() | |
| res = server.make_request("POST", "/completion", data={ | |
| "prompt": "I believe the meaning of life is", | |
| "temperature": 0.0, | |
| "top_k": 1, | |
| "n_predict": 16, | |
| }) | |
| assert res.status_code == 200 | |
| content_draft = res.body["content"] | |
| assert content_no_draft == content_draft | |
| def test_different_draft_min_draft_max(): | |
| global server | |
| test_values = [ | |
| (1, 2), | |
| (1, 4), | |
| (4, 8), | |
| (4, 12), | |
| (8, 16), | |
| ] | |
| last_content = None | |
| for draft_min, draft_max in test_values: | |
| server.stop() | |
| server.draft_min = draft_min | |
| server.draft_max = draft_max | |
| server.start() | |
| res = server.make_request("POST", "/completion", data={ | |
| "prompt": "I believe the meaning of life is", | |
| "temperature": 0.0, | |
| "top_k": 1, | |
| "n_predict": 16, | |
| }) | |
| assert res.status_code == 200 | |
| if last_content is not None: | |
| assert last_content == res.body["content"] | |
| last_content = res.body["content"] | |
| def test_slot_ctx_not_exceeded(): | |
| global server | |
| server.n_ctx = 256 | |
| server.start() | |
| res = server.make_request("POST", "/completion", data={ | |
| "prompt": "Hello " * 248, | |
| "temperature": 0.0, | |
| "top_k": 1, | |
| "speculative.p_min": 0.0, | |
| }) | |
| assert res.status_code == 200 | |
| assert len(res.body["content"]) > 0 | |
| def test_with_ctx_shift(): | |
| global server | |
| server.n_ctx = 256 | |
| server.enable_ctx_shift = True | |
| server.start() | |
| res = server.make_request("POST", "/completion", data={ | |
| "prompt": "Hello " * 248, | |
| "temperature": 0.0, | |
| "top_k": 1, | |
| "n_predict": 256, | |
| "speculative.p_min": 0.0, | |
| }) | |
| assert res.status_code == 200 | |
| assert len(res.body["content"]) > 0 | |
| assert res.body["tokens_predicted"] == 256 | |
| assert res.body["truncated"] == True | |
| def test_multi_requests_parallel(n_slots: int, n_requests: int): | |
| global server | |
| server.n_slots = n_slots | |
| server.start() | |
| tasks = [] | |
| for _ in range(n_requests): | |
| tasks.append((server.make_request, ("POST", "/completion", { | |
| "prompt": "I believe the meaning of life is", | |
| "temperature": 0.0, | |
| "top_k": 1, | |
| }))) | |
| results = parallel_function_calls(tasks) | |
| for res in results: | |
| assert res.status_code == 200 | |
| assert match_regex("(wise|kind|owl|answer)+", res.body["content"]) | |