Spaces:
Running
on
Zero
Running
on
Zero
gpu
Browse files
modular_graph_and_candidates.py
CHANGED
@@ -40,6 +40,7 @@ from typing import Dict, List, Set, Tuple
|
|
40 |
from sentence_transformers import SentenceTransformer, util
|
41 |
from tqdm import tqdm
|
42 |
import numpy as np
|
|
|
43 |
|
44 |
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
45 |
# CONFIG
|
@@ -93,6 +94,7 @@ def similarity_clusters(bags: Dict[str, List[Set[str]]], thr: float) -> Dict[Tup
|
|
93 |
out[(m1, m2)] = s
|
94 |
return out
|
95 |
|
|
|
96 |
def embedding_similarity_clusters(models_root: Path, missing: List[str], thr: float) -> Dict[Tuple[str, str], float]:
|
97 |
model = SentenceTransformer("nomic-ai/nomic-embed-code")
|
98 |
model.max_seq_length = 4096 # truncate overly long modeling files
|
|
|
40 |
from sentence_transformers import SentenceTransformer, util
|
41 |
from tqdm import tqdm
|
42 |
import numpy as np
|
43 |
+
import spaces
|
44 |
|
45 |
# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
|
46 |
# CONFIG
|
|
|
94 |
out[(m1, m2)] = s
|
95 |
return out
|
96 |
|
97 |
+
@spaces.GPU
|
98 |
def embedding_similarity_clusters(models_root: Path, missing: List[str], thr: float) -> Dict[Tuple[str, str], float]:
|
99 |
model = SentenceTransformer("nomic-ai/nomic-embed-code")
|
100 |
model.max_seq_length = 4096 # truncate overly long modeling files
|