Feature Extraction
Transformers
Safetensors
lfm2
fill-mask
encoder-only
multimodal
image-text-retrieval
image-text-matching
siglip2
lfm2.5
gptq
custom_code
compressed-tensors
Instructions to use konic-labs/LFM2.5-multimodal-encoder-230M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use konic-labs/LFM2.5-multimodal-encoder-230M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="konic-labs/LFM2.5-multimodal-encoder-230M", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("konic-labs/LFM2.5-multimodal-encoder-230M", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("konic-labs/LFM2.5-multimodal-encoder-230M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": "outputs/monet-100k/compression-gptq-int4-clean", | |
| "vision_model": "google/siglip2-base-patch16-256", | |
| "device": "cuda:0", | |
| "dtype": "torch.float32", | |
| "setup": { | |
| "model_load_ms": 1752.9155970041757, | |
| "vision_load_ms": 689.1005889992812 | |
| }, | |
| "model_parameter_count": 230963108, | |
| "model_bytes": 370447122, | |
| "pairs": "/data/datasets/monet-100k/test_pairs.jsonl", | |
| "projector_checkpoint": "outputs/monet-100k/retrieval-matching-clean/multimodal_task_adapter.pt", | |
| "text": { | |
| "iterations": 10, | |
| "warmup": 3, | |
| "latency_ms_mean": 16.75748469933751, | |
| "latency_ms_median": 16.738547001295956, | |
| "latency_ms_p95": 17.114150999987032, | |
| "latency_ms_min": 16.403875000833068, | |
| "latency_ms_max": 17.172412997751962, | |
| "peak_vram_bytes": 1049502720, | |
| "batch_size": 4, | |
| "sequence_length": 53, | |
| "hidden_shape": [ | |
| 4, | |
| 53, | |
| 1024 | |
| ], | |
| "logits_shape": [ | |
| 4, | |
| 53, | |
| 65536 | |
| ], | |
| "finite_hidden": true, | |
| "finite_logits": true | |
| }, | |
| "multimodal": { | |
| "body_only": { | |
| "iterations": 10, | |
| "warmup": 3, | |
| "latency_ms_mean": 18.0679445998976, | |
| "latency_ms_median": 18.043951498839306, | |
| "latency_ms_p95": 18.232377005915623, | |
| "latency_ms_min": 17.939090001164004, | |
| "latency_ms_max": 18.2529970043106, | |
| "peak_vram_bytes": 2531130880 | |
| }, | |
| "vision_plus_body": { | |
| "iterations": 10, | |
| "warmup": 3, | |
| "latency_ms_mean": 45.672791600372875, | |
| "latency_ms_median": 45.429460500599816, | |
| "latency_ms_p95": 46.00368000683375, | |
| "latency_ms_min": 44.96823700173991, | |
| "latency_ms_max": 47.790171003725845, | |
| "peak_vram_bytes": 2552086016 | |
| }, | |
| "vision_features_shape": [ | |
| 4, | |
| 256, | |
| 768 | |
| ], | |
| "image_tokens_shape": [ | |
| 4, | |
| 32, | |
| 1024 | |
| ], | |
| "fused_shape": [ | |
| 4, | |
| 86, | |
| 1024 | |
| ], | |
| "hidden_shape": [ | |
| 4, | |
| 86, | |
| 1024 | |
| ], | |
| "image_marker_position": 1, | |
| "finite_hidden": true | |
| }, | |
| "note": "Multimodal path uses the supplied trained projector; matching-head scoring is not timed." | |
| } | |