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
Download sentence_bert_config.json from LCO-Embedding/LCO-Embedding-Omni-7B: direct link, hf CLI and curl.
- Browser
- Download file 1.15 kB
-
https://huggingface.co/LCO-Embedding/LCO-Embedding-Omni-7B/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://LCO-Embedding/LCO-Embedding-Omni-7B/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/LCO-Embedding/LCO-Embedding-Omni-7B/resolve/main/sentence_bert_config.json
1.15 kB
| { | |
| "transformer_task": "any-to-any", | |
| "modality_config": { | |
| "text": { | |
| "method": "forward", | |
| "method_output_name": [ | |
| "hidden_states", | |
| -1 | |
| ] | |
| }, | |
| "image": { | |
| "method": "forward", | |
| "method_output_name": [ | |
| "hidden_states", | |
| -1 | |
| ] | |
| }, | |
| "audio": { | |
| "method": "forward", | |
| "method_output_name": [ | |
| "hidden_states", | |
| -1 | |
| ] | |
| }, | |
| "video": { | |
| "method": "forward", | |
| "method_output_name": [ | |
| "hidden_states", | |
| -1 | |
| ] | |
| }, | |
| "message": { | |
| "method": "forward", | |
| "method_output_name": [ | |
| "hidden_states", | |
| -1 | |
| ], | |
| "format": "structured" | |
| } | |
| }, | |
| "module_output_name": "token_embeddings", | |
| "processing_kwargs": { | |
| "chat_template": { | |
| "chat_template": "sentence_transformers", | |
| "add_generation_prompt": true | |
| } | |
| } | |
| } |