Instructions to use mlx-community/LFM2-700M-5bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/LFM2-700M-5bit 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("mlx-community/LFM2-700M-5bit") 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
- LM Studio
- MLX LM
How to use mlx-community/LFM2-700M-5bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/LFM2-700M-5bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/LFM2-700M-5bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/LFM2-700M-5bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
| { | |
| "architectures": [ | |
| "Lfm2ForCausalLM" | |
| ], | |
| "block_auto_adjust_ff_dim": true, | |
| "block_dim": 1536, | |
| "block_ff_dim": 10240, | |
| "block_ffn_dim_multiplier": 1.0, | |
| "block_mlp_init_scale": 1.0, | |
| "block_multiple_of": 256, | |
| "block_norm_eps": 1e-05, | |
| "block_out_init_scale": 1.0, | |
| "block_use_swiglu": true, | |
| "block_use_xavier_init": true, | |
| "bos_token_id": 1, | |
| "conv_L_cache": 3, | |
| "conv_bias": false, | |
| "conv_dim": 1536, | |
| "conv_dim_out": 1536, | |
| "conv_use_xavier_init": true, | |
| "eos_token_id": 7, | |
| "full_attn_idxs": [ | |
| 2, | |
| 5, | |
| 8, | |
| 10, | |
| 12, | |
| 14 | |
| ], | |
| "hidden_size": 1536, | |
| "initializer_range": 0.02, | |
| "max_position_embeddings": 128000, | |
| "model_type": "lfm2", | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 24, | |
| "num_heads": 24, | |
| "num_hidden_layers": 16, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 0, | |
| "quantization": { | |
| "group_size": 64, | |
| "bits": 5 | |
| }, | |
| "quantization_config": { | |
| "group_size": 64, | |
| "bits": 5 | |
| }, | |
| "rope_theta": 1000000.0, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.54.0.dev0", | |
| "use_cache": true, | |
| "use_pos_enc": true, | |
| "vocab_size": 65536 | |
| } |