Instructions to use N8Programs/talkie-box with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use N8Programs/talkie-box with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("N8Programs/talkie-box") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use N8Programs/talkie-box with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "N8Programs/talkie-box"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "N8Programs/talkie-box" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "N8Programs/talkie-box", "messages": [ {"role": "user", "content": "Hello"} ] }'
File size: 519 Bytes
b8bde03 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"architectures": [
"TalkieForCausalLM"
],
"eos_token_id": [
65535,
56180
],
"head_dim": 128,
"hidden_size": 5120,
"intermediate_size": 13696,
"max_position_embeddings": 2048,
"model_file": "talkie_mlx.py",
"num_attention_heads": 40,
"num_hidden_layers": 40,
"pad_token_id": 65535,
"rms_norm_eps": 1.1920928955078125e-07,
"rope_theta": 1000000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"vocab_size": 65536
}
|