Feature Extraction
sentence-transformers
PyTorch
Safetensors
Transformers
English
bert
Phrase Representation
String Matching
Fuzzy Join
Entity Retrieval
text-embeddings-inference
Instructions to use Lihuchen/pearl_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Lihuchen/pearl_small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Lihuchen/pearl_small") 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 Lihuchen/pearl_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Lihuchen/pearl_small")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Lihuchen/pearl_small") model = AutoModel.from_pretrained("Lihuchen/pearl_small") - Notebooks
- Google Colab
- Kaggle
Tom Aarsen commited on
Commit ·
e5f16c7
1
Parent(s): 071e1bb
Reduce to Sentence Transformers 2.3.1
Browse files(Otherwise people will get warnings as 2.4.0 isn't out yet for a few more days)
config_sentence_transformers.json
CHANGED
|
@@ -1,9 +1,7 @@
|
|
| 1 |
{
|
| 2 |
"__version__": {
|
| 3 |
-
"sentence_transformers": "2.
|
| 4 |
"transformers": "4.37.0",
|
| 5 |
"pytorch": "2.1.0+cu121"
|
| 6 |
-
}
|
| 7 |
-
"prompts": {},
|
| 8 |
-
"default_prompt_name": null
|
| 9 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"__version__": {
|
| 3 |
+
"sentence_transformers": "2.3.1",
|
| 4 |
"transformers": "4.37.0",
|
| 5 |
"pytorch": "2.1.0+cu121"
|
| 6 |
+
}
|
|
|
|
|
|
|
| 7 |
}
|