Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
qwen2
text-generation
mteb
custom_code
Eval Results (legacy)
text-embeddings-inference
Instructions to use blevlabs/stella_en_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use blevlabs/stella_en_v5 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("blevlabs/stella_en_v5", trust_remote_code=True) sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use blevlabs/stella_en_v5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("blevlabs/stella_en_v5", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("blevlabs/stella_en_v5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download modules.json from blevlabs/stella_en_v5: direct link, hf CLI and curl.
- Browser
- Download file 316 Bytes
-
https://huggingface.co/blevlabs/stella_en_v5/resolve/main/modules.json
- Command line
-
hf download hf://blevlabs/stella_en_v5/modules.json
-
curl -L -o modules.json https://huggingface.co/blevlabs/stella_en_v5/resolve/main/modules.json
316 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Dense_1024", | |
| "type": "sentence_transformers.models.Dense" | |
| } | |
| ] |