Feature Extraction
sentence-transformers
Safetensors
Transformers
English
mistraldual
sentence-similarity
custom_code
Instructions to use GeoGPT-Research-Project/GeoEmbedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GeoGPT-Research-Project/GeoEmbedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GeoGPT-Research-Project/GeoEmbedding", trust_remote_code=True) 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 GeoGPT-Research-Project/GeoEmbedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="GeoGPT-Research-Project/GeoEmbedding", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("GeoGPT-Research-Project/GeoEmbedding", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 624 Bytes
7732666 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"additional_special_tokens": [
"<unk>",
"<s>",
"</s>"
],
"bos_token": {
"content": "<s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"eos_token": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"pad_token": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"unk_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
}
|