Instructions to use mlx-community/CodeFormulaV2-mlx-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/CodeFormulaV2-mlx-bf16 with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("mlx-community/CodeFormulaV2-mlx-bf16") config = load_config("mlx-community/CodeFormulaV2-mlx-bf16") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
| { | |
| "_flash_attn_2_enabled": true, | |
| "architectures": [ | |
| "Idefics3ForConditionalGeneration" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 100264, | |
| "eos_token_id": 100338, | |
| "freeze_lm_head": true, | |
| "freeze_text_layers": true, | |
| "freeze_text_module_exceptions": [], | |
| "freeze_vision_layers": true, | |
| "freeze_vision_module_exceptions": [], | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 576, | |
| "image_token_id": 100270, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "model_type": "idefics3", | |
| "neftune_noise_alpha": 0.0, | |
| "num_attention_heads": 9, | |
| "num_hidden_layers": 30, | |
| "num_key_value_heads": 3, | |
| "pad_token_id": 100256, | |
| "perceiver_config": { | |
| "attention_dropout": 0.0, | |
| "hidden_act": "silu", | |
| "model_type": "vllama3", | |
| "num_key_value_heads": 1, | |
| "qk_layer_norms_perceiver": false, | |
| "resampler_depth": 6, | |
| "resampler_head_dim": 96, | |
| "resampler_n_heads": 16, | |
| "resampler_n_latents": 64 | |
| }, | |
| "pixel_shuffle_factor": 4, | |
| "pretraining_tp": 1, | |
| "qk_layer_norms": false, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 100000.0, | |
| "scale_factor": 4, | |
| "text_config": { | |
| "architectures": [ | |
| "VLlama3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 100257, | |
| "eos_token_id": 100257, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 576, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 9, | |
| "num_hidden_layers": 30, | |
| "num_key_value_heads": 3, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "torch_dtype": "bfloat16", | |
| "use_cache": true, | |
| "vocab_size": 100480, | |
| "tie_word_embeddings": false | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "4.51.3", | |
| "use_cache": false, | |
| "use_resampler": false, | |
| "vision_config": { | |
| "attention_dropout": 0.0, | |
| "hidden_act": "gelu_pytorch_tanh", | |
| "hidden_size": 768, | |
| "image_size": 512, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "layer_norm_eps": 1e-06, | |
| "max_image_size": { | |
| "longest_edge": 512 | |
| }, | |
| "model_type": "idefics3_vision", | |
| "num_attention_heads": 12, | |
| "num_channels": 3, | |
| "num_hidden_layers": 12, | |
| "patch_size": 16, | |
| "size": { | |
| "longest_edge": 2048 | |
| }, | |
| "torch_dtype": "bfloat16", | |
| "use_base_siglip": true | |
| }, | |
| "vocab_size": 100480 | |
| } |