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: 4,376 Bytes
15c3607 | 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 | import { describe, expect, it } from 'vitest';
import { parseHeadersToArray, serializeHeaders } from '$lib/utils/headers';
/**
* Tests for the header serialization helpers used by the MCP server form
* (custom header rows) and the new Authorization/Bearer-token flow.
*/
describe('parseHeadersToArray', () => {
it('returns an empty array for empty or whitespace-only input', () => {
expect(parseHeadersToArray('')).toEqual([]);
expect(parseHeadersToArray(' ')).toEqual([]);
expect(parseHeadersToArray(undefined as unknown as string)).toEqual([]);
});
it('returns an empty array for invalid JSON input', () => {
expect(parseHeadersToArray('{not-json')).toEqual([]);
expect(parseHeadersToArray('[]')).toEqual([]);
expect(parseHeadersToArray('"plain-string"')).toEqual([]);
});
it('converts an object into ordered key/value pairs', () => {
expect(parseHeadersToArray('{"X-Foo":"bar","Authorization":"Bearer abc"}')).toEqual([
{ key: 'X-Foo', value: 'bar' },
{ key: 'Authorization', value: 'Bearer abc' }
]);
});
it('stringifies non-string values', () => {
expect(parseHeadersToArray('{"count":"42","flag":"true"}')).toEqual([
{ key: 'count', value: '42' },
{ key: 'flag', value: 'true' }
]);
});
});
describe('serializeHeaders', () => {
it('returns an empty string when there are no valid pairs', () => {
expect(serializeHeaders([])).toBe('');
expect(serializeHeaders([{ key: '', value: 'value' }])).toBe('');
expect(serializeHeaders([{ key: ' ', value: 'value' }])).toBe('');
});
it('returns an empty string when every pair has a blank key', () => {
expect(
serializeHeaders([
{ key: '', value: 'drop-me' },
{ key: ' ', value: 'drop-me-too' },
{ key: '\t', value: 'tab-key' }
])
).toBe('');
});
it('drops pairs with empty keys but keeps the rest', () => {
expect(
serializeHeaders([
{ key: '', value: 'drop-me' },
{ key: 'X-Keep', value: 'ok' }
])
).toBe('{"X-Keep":"ok"}');
});
it('trims keys before serializing', () => {
expect(serializeHeaders([{ key: ' X-Space ', value: 'ok' }])).toBe('{"X-Space":"ok"}');
});
it('preserves the input order of surviving pairs', () => {
const serialized = serializeHeaders([
{ key: 'X-C', value: '3' },
{ key: 'X-A', value: '1' },
{ key: 'X-B', value: '2' }
]);
// Object key order follows insertion order in modern JS engines, so
// the serialized JSON writes keys in our input order.
expect(JSON.parse(serialized)).toEqual({ 'X-C': '3', 'X-A': '1', 'X-B': '2' });
});
});
describe('parseHeadersToArray / serializeHeaders roundtrip', () => {
it('serializes back to an equal header object after a parse', () => {
const original = JSON.stringify({
'Content-Type': 'application/json',
'X-Trace-Id': 'abc-123'
});
const roundtrip = serializeHeaders(parseHeadersToArray(original));
expect(JSON.parse(roundtrip)).toEqual(JSON.parse(original));
});
it('drops rows whose keys are blank after trimming during serialization', () => {
const pairs = parseHeadersToArray('{"X-Keep":"ok","":"drop-me"}');
// parseHeadersToArray keeps raw key strings (the consumer is expected to
// filter blanks, not the parser); serialization must strip them.
expect(pairs).toEqual([
{ key: 'X-Keep', value: 'ok' },
{ key: '', value: 'drop-me' }
]);
expect(serializeHeaders(pairs)).toBe('{"X-Keep":"ok"}');
});
it('preserves upstream keys untouched (does not lowercase them)', () => {
const upperCased = '{"Authorization":"Bearer xyz"}';
const parsed = parseHeadersToArray(upperCased);
expect(parsed).toEqual([{ key: 'Authorization', value: 'Bearer xyz' }]);
});
it('bearer-token write survives a re-parse when paired with regular custom headers', () => {
// The McpServerForm bearer UI writes {Authorization: `Bearer <token>`}
// into the same headers string as the custom KV section. The round
// trip below mirrors the exact shape the form produces so a future
// refactor of either code path cannot silently change the on-disk key.
const pairs = [
{ key: 'X-Trace-Id', value: 'abc-123' },
{ key: 'Authorization', value: 'Bearer super-secret' }
];
const serialized = serializeHeaders(pairs);
expect(serialized).toBe('{"X-Trace-Id":"abc-123","Authorization":"Bearer super-secret"}');
expect(parseHeadersToArray(serialized)).toEqual(pairs);
});
});
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