-
To more explicitly test all possible meanings of them. When you play codenames, you try to give more equal consideration to obscure meanings of words and to common ones than you'd normally do.
-
Hi all — thanks for all your work on this package and documentation. I’m just getting into word embeddings and all of your resources have been incredibly helpful.
I was excited to see the new “get…
-
### Microsoft PowerToys version
0.79.0
### Installation method
WinGet
### Running as admin
Yes
### Area(s) with issue?
Peek
### Steps to reproduce
1. Open a folder in File Explorer with Previ…
pa-0 updated
6 months ago
-
Hi!
I tried your model because mine is not very good in sense addition like king+woman-man=queen the classic example for word2vec.
So I tried:
βασιλεύς + γυνή - ἀνήρ = γνόφον σπέρματί εἰσελεύσ…
-
try using word vector simliarities, at least put a threshold in there below which it fails
-
1. Base agent class (to extend by other people)
2. Readable code :)
3. agent base class to export a function that can get a board with tags,, and return a word and number
-
I notice the fine-grained contrastive loss takes the average of embeddings of words, which are top-k related with a clip, as positive word representation and other in-batch words as negative samples. …
-
请问汉语语义法相似度和字面编辑法相似度分别采用的是什么算法进行计算的
-
大大你好,运行速度上好像有点问题
MIPP tests
----------
Instr. type: AVX
Instr. full type: AVX2
Instr. version: 2
Instr. size: 256 bits
Instr. lanes: 2
64-bit support: yes
Byte/word …
-
In explore_context2vec.py, when got context_v and target_v, why use w again?
You use the w to get the context_v, didn't you?
```
def mult_sim(w, target_v, context_v):
target_similarity = w.dot…
mfxss updated
6 years ago