Text Generation
MLX
English
lora
apple-silicon
cx
crm
lam
large-action-model
customer-experience
tool-calling
qwen2.5
0.5b
local
iterative
agentic
multi-turn
Instructions to use chendren/qwen2.5-0.5b-cx-lam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use chendren/qwen2.5-0.5b-cx-lam 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("chendren/qwen2.5-0.5b-cx-lam") 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 chendren/qwen2.5-0.5b-cx-lam with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "chendren/qwen2.5-0.5b-cx-lam" --prompt "Once upon a time"
- Atomic Chat
Ctrl+K
Update to iterative closed-loop LAM: retrained 300 iters on step-by-step data using build_continuation_prompt. Now supports true multi-turn via one-action-per-step + feedback. Updated model card with new usage, evaluation (100% success in 10 iterative tests), and architecture details. Includes retrained adapters.
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