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"
- Atomic Chat
Commit History
-
Update README.md
Verified signature5410040 -
Update README.md
Verified signature040e6c3 -
Update README.md
Verified signaturee6150cf -
Update README.md
Verified signaturea3b18c7 -
Upload chat_stage_b.py with huggingface_hub
Verified signatureac8476e -
Upload tokenizer/leek_bpe_32k.vocab with huggingface_hub
Verified signature85da6d4 -
Upload tokenizer/leek_bpe_32k.model with huggingface_hub
Verified signature95f41d4 -
Upload leeknet_500m.py with huggingface_hub
Verified signaturef6e3ff4 -
Upload stage_b_step15250_best.npz with huggingface_hub
Verified signature207e44b -
Update README.md
Verified signaturead79318 -
Update README.md
Verified signature9115bb0 -
initial commit
Verified signaturecd98eb4