Text Generation
MLX
English
mamba
ssm
hybrid
transformer
from-scratch
custom-architecture
apple-silicon
Instructions to use TreeLeek/TCF-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TreeLeek/TCF-1 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("TreeLeek/TCF-1") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use TreeLeek/TCF-1 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "TreeLeek/TCF-1" --prompt "Once upon a time"
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- stage_b_step15250_best.npz — 1.98 GB weights
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- leeknet_500m.py — architecture
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- chat_stage_b.py — chat interface
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- tokenizer/leek_bpe_32k.model — SentencePiece model
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- tokenizer/leek_bpe_32k.vocab — vocabulary
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