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.
- 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
File size: 6,309 Bytes
8efb28e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 | import pytest
from openai import OpenAI
from utils import *
import threading
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
server = ServerPreset.tinyllama2()
TEST_API_KEY = "sk-this-is-the-secret-key"
@pytest.fixture(autouse=True)
def create_server():
global server
server = ServerPreset.tinyllama2()
server.api_key = TEST_API_KEY
@pytest.mark.parametrize("endpoint", ["/health", "/models"])
def test_access_public_endpoint(endpoint: str):
global server
server.start()
res = server.make_request("GET", endpoint)
assert res.status_code == 200
assert "error" not in res.body
def test_access_static_assets_without_api_key():
"""Static web UI assets should not require API key authentication (issue #21229)"""
global server
server.start()
for path in ["/", "/sw.js", "/manifest.webmanifest", "/_app/version.json"]:
res = server.make_request("GET", path)
assert res.status_code == 200, f"Expected 200 for {path}, got {res.status_code}"
@pytest.mark.parametrize("api_key", [None, "invalid-key"])
def test_incorrect_api_key(api_key: str):
global server
server.start()
res = server.make_request("POST", "/completions", data={
"prompt": "I believe the meaning of life is",
}, headers={
"Authorization": f"Bearer {api_key}" if api_key else None,
})
assert res.status_code == 401
assert "error" in res.body
assert res.body["error"]["type"] == "authentication_error"
def test_correct_api_key():
global server
server.start()
res = server.make_request("POST", "/completions", data={
"prompt": "I believe the meaning of life is",
}, headers={
"Authorization": f"Bearer {TEST_API_KEY}",
})
assert res.status_code == 200
assert "error" not in res.body
assert "content" in res.body
def test_correct_api_key_anthropic_header():
global server
server.start()
res = server.make_request("POST", "/completions", data={
"prompt": "I believe the meaning of life is",
}, headers={
"X-Api-Key": TEST_API_KEY,
})
assert res.status_code == 200
assert "error" not in res.body
assert "content" in res.body
def test_openai_library_correct_api_key():
global server
server.start()
client = OpenAI(api_key=TEST_API_KEY, base_url=f"http://{server.server_host}:{server.server_port}")
res = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a chatbot."},
{"role": "user", "content": "What is the meaning of life?"},
],
)
assert len(res.choices) == 1
@pytest.mark.parametrize("origin,cors_header,cors_header_value", [
("localhost", "Access-Control-Allow-Origin", "localhost"),
("web.mydomain.fr", "Access-Control-Allow-Origin", "web.mydomain.fr"),
("origin", "Access-Control-Allow-Credentials", "true"),
("web.mydomain.fr", "Access-Control-Allow-Methods", "GET, POST"),
("web.mydomain.fr", "Access-Control-Allow-Headers", "*"),
])
def test_cors_options(origin: str, cors_header: str, cors_header_value: str):
global server
server.start()
res = server.make_request("OPTIONS", "/completions", headers={
"Origin": origin,
"Access-Control-Request-Method": "POST",
"Access-Control-Request-Headers": "Authorization",
})
assert res.status_code == 200
assert cors_header in res.headers
assert res.headers[cors_header] == cors_header_value
def test_cors_proxy_only_forwards_explicit_proxy_headers():
class CaptureHeadersHandler(BaseHTTPRequestHandler):
def do_GET(self):
self.server.captured_headers = dict(self.headers)
self.send_response(200)
self.end_headers()
self.wfile.write(b"ok")
def log_message(self, format, *args):
pass
target = ThreadingHTTPServer(("127.0.0.1", 0), CaptureHeadersHandler)
target.captured_headers = {}
target_thread = threading.Thread(target=target.serve_forever, daemon=True)
target_thread.start()
try:
server = ServerPreset.tinyllama2()
server.api_key = TEST_API_KEY
server.ui_mcp_proxy = True
server.start()
res = server.make_request("GET", f"/cors-proxy?url=http://127.0.0.1:{target.server_port}/capture", headers={
"Authorization": f"Bearer {TEST_API_KEY}",
"Proxy-Authorization": "Basic secret",
"X-Api-Key": TEST_API_KEY,
"Cookie": "session=secret",
"x-llama-server-proxy-header-accept": "application/json",
"x-llama-server-proxy-header-authorization": "Bearer explicit",
})
assert res.status_code == 200
captured = {key.lower(): value for key, value in target.captured_headers.items()}
assert captured["accept"] == "application/json"
assert captured["authorization"] == "Bearer explicit"
assert "proxy-authorization" not in captured
assert "x-api-key" not in captured
assert "cookie" not in captured
finally:
target.shutdown()
target.server_close()
@pytest.mark.parametrize(
"media_path, image_url, success",
[
(None, "file://mtmd/test-1.jpeg", False), # disabled media path, should fail
("../../../tools", "file://mtmd/test-1.jpeg", True),
("../../../tools", "file:////mtmd//test-1.jpeg", True), # should be the same file as above
("../../../tools", "file://mtmd/notfound.jpeg", False), # non-existent file
("../../../tools", "file://../mtmd/test-1.jpeg", False), # no directory traversal
]
)
def test_local_media_file(media_path, image_url, success,):
server = ServerPreset.tinygemma3()
server.media_path = media_path
server.start()
res = server.make_request("POST", "/chat/completions", data={
"max_tokens": 1,
"messages": [
{"role": "user", "content": [
{"type": "text", "text": "test"},
{"type": "image_url", "image_url": {
"url": image_url,
}},
]},
],
})
if success:
assert res.status_code == 200
else:
assert res.status_code == 400
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