---
license: mit
datasets:
- silicone
---

This `KeyedVectors` model is specifically for `silicone:dyda_da`

*you must download both the `.wordvectors` and `.wordvectors.npy` files

```python
from gensim.models.keyedvectors import KeyedVectors

kv=KeyedVectors.load("silicone-dyda_da-utterance-tokens.wordvectors")

print(model.wv.most_similar_cosmul('peter',topn=25))

[('steven', 0.889095664024353),
 ('alice', 0.8783409595489502),
 ('li', 0.8624751567840576),
 ('benjamin', 0.8622595071792603),
 ('mrs', 0.8615201711654663),
 ('lin', 0.8603521585464478),
 ('david', 0.8597986698150635),
 ('dr', 0.8588740825653076),
 ('wang', 0.8527941107749939),
 ('mary', 0.8522424697875977),
 ('mike', 0.8521847724914551),
 ('john', 0.8494851589202881),
 ('michael', 0.84917151927948),
 ('linda', 0.8488836288452148),
 ('lucy', 0.8375136256217957),
 ('jane', 0.8359535336494446),
 ('monica', 0.834464430809021),
 ('smith', 0.8331072926521301),
 ('susan', 0.8329276442527771),
 ('zhang', 0.8323286771774292),
 ('professor', 0.8316935896873474),
 ('ellen', 0.8311569094657898),
 ('daniel', 0.8285720944404602),
 ('charles', 0.8285550475120544),
 ('james', 0.8280013203620911)]
```