Sentence Similarity
sentence-transformers
ONNX
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use MintplexLabs/multilingual-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use MintplexLabs/multilingual-e5-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("MintplexLabs/multilingual-e5-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] - Notebooks
- Google Colab
- Kaggle
File size: 1,117 Bytes
b610752 b0688c5 b610752 6981847 | 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 | from huggingface_hub import HfApi
import os
REPO_ID = "MintplexLabs/multilingual-e5-small"
LOCAL_PATH = "." # your local directory
api = HfApi()
# Get list of files in repo
remote_files = {f for f in api.list_repo_files(repo_id=REPO_ID)}
# Delete .DS_Store files if present in remote
ds_store_files = {f for f in remote_files if f.endswith('.DS_Store')}
for file in ds_store_files:
print(f"Deleting {file} from repo...")
api.delete_file(path_in_repo=file, repo_id=REPO_ID)
# Get list of files locally (recursively)
local_files = set()
for root, _, files in os.walk(LOCAL_PATH):
for file in files:
full_path = os.path.join(root, file)
relative_path = os.path.relpath(full_path, LOCAL_PATH)
local_files.add(relative_path.replace("\\", "/"))
# Find files that exist remotely but not locally
files_to_delete = remote_files - local_files
# Delete them
for file in files_to_delete:
print(f"Deleting {file} from repo...")
api.delete_file(path_in_repo=file, repo_id=REPO_ID)
# Now re-upload local files using the CLI
print(f"huggingface-cli upload {REPO_ID} {LOCAL_PATH}") |