Feature Extraction
sentence-transformers
Safetensors
Transformers
qwen2_5_omni_thinker
image-text-to-text
multimodal-embedding
Instructions to use LCO-Embedding/LCO-Embedding-Omni-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LCO-Embedding/LCO-Embedding-Omni-7B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LCO-Embedding/LCO-Embedding-Omni-7B") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use LCO-Embedding/LCO-Embedding-Omni-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LCO-Embedding/LCO-Embedding-Omni-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("LCO-Embedding/LCO-Embedding-Omni-7B") model = AutoModelForMultimodalLM.from_pretrained("LCO-Embedding/LCO-Embedding-Omni-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "</tool_call>": 151658, | |
| "<tool_call>": 151657, | |
| "<|AUDIO|>": 151646, | |
| "<|IMAGE|>": 151655, | |
| "<|VIDEO|>": 151656, | |
| "<|audio_bos|>": 151647, | |
| "<|audio_eos|>": 151648, | |
| "<|box_end|>": 151649, | |
| "<|endoftext|>": 151643, | |
| "<|file_sep|>": 151664, | |
| "<|fim_middle|>": 151660, | |
| "<|fim_pad|>": 151662, | |
| "<|fim_prefix|>": 151659, | |
| "<|fim_suffix|>": 151661, | |
| "<|im_end|>": 151645, | |
| "<|im_start|>": 151644, | |
| "<|quad_end|>": 151651, | |
| "<|quad_start|>": 151650, | |
| "<|repo_name|>": 151663, | |
| "<|vision_bos|>": 151652, | |
| "<|vision_eos|>": 151653, | |
| "<|vision_pad|>": 151654 | |
| } | |