github
/
ChatGLM-6B
mirror of https://github.com/THUDM/ChatGLM-6B
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

Remove qe model

Browse Source
pull/573/head
duzx16 2 years ago
parent 70e015654c
commit 7410cacd91
1 changed files with 0 additions and 5 deletions
Show Stats Download Patch File Download Diff File

5
README_en.md
Unescape View File

@ -140,11 +140,6 @@ Model quantization brings a certain performance decline. After testing, ChatGLM-
model = AutoModel.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True).half().cuda() model = AutoModel.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True).half().cuda()
``` ```
**[2023/03/24]** We further provide an embedding-quantized model whose model parameters only cost 4.3GB GPU memory
```python
model = AutoModel.from_pretrained("THUDM/chatglm-6b-int4-qe", trust_remote_code=True).half().cuda()
```
### CPU Deployment ### CPU Deployment
If your computer is not equipped with GPU, you can also conduct inference on CPU, but the inference speed is slow (and taking about 32GB of memory): If your computer is not equipped with GPU, you can also conduct inference on CPU, but the inference speed is slow (and taking about 32GB of memory):

Write Preview
Loading…
Cancel
Save