Skip to content

Commit e3b949b

Browse files
authored
Merge pull request #872 from willtaner/T4_docs
T4 docs
2 parents 90d0594 + 3ba052d commit e3b949b

File tree

2 files changed

+23
-0
lines changed

2 files changed

+23
-0
lines changed

docs/community/faq.md

Lines changed: 12 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -177,3 +177,15 @@ library.add_files(input_foler_path=Path('~/llmware_data/sample_files/Agreements'
177177
library.install_new_embedding(embedding_model_name='mini-lm-sber')
178178
library.install_new_embedding(embedding_model_name='industry-bert-contracts')
179179
```
180+
181+
### Why is the model running slowly in Google Colab?
182+
#### "I want to improve the performance of my model on Google Colab"
183+
184+
Our models are designed to run on at least 16GB of RAM. By default Google Colab provides ~13GB of RAM, which significantly slows computational speed. To ensure the best performance when using our models, we highly recommend enabling the T4 GPU in Colab. This will provide the notebook with additional resources, including 16GB of RAM, allowing our models to run smoothly and efficiently.
185+
186+
Steps to enabling T4 GPU in Colab:
187+
1. In your Colab notebook, click on the "Runtime" tab
188+
2. Select "Change runtime type"
189+
3. Under "Hardware Accelerator", select T4 GPU
190+
191+
NOTE: There is a weekly usage limit on using T4 for free.

docs/examples/notebooks.md

Lines changed: 11 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -27,6 +27,17 @@ Google Colab (or Colaboratory) is a free Jupyter notebook environment that requi
2727
- **Language Support:** Primarily, both are used for executing Python code. However, Jupyter Notebooks support other languages such as R and Julia.
2828
- **Use Cases:** They are widely used for data analysis, machine learning, and education, allowing for easy sharing of results and methodologies.
2929

30+
## Increase Google Colab Computational Power with T4 GPU
31+
32+
Our models are designed to run on at least 16GB of RAM. By default Google Colab provides ~13GB of RAM, which significantly slows computational speed. To ensure the best performance when using our models, we highly recommend enabling the T4 GPU in Colab. This will provide the notebook with additional resources, including 16GB of RAM, allowing our models to run smoothly and efficiently.
33+
34+
Steps to enabling T4 GPU in Colab:
35+
1. In your Colab notebook, click on the "Runtime" tab
36+
2. Select "Change runtime type"
37+
3. Under "Hardware Accelerator", select T4 GPU
38+
39+
NOTE: There is a weekly usage limit on using T4 for free.
40+
3041
## Key Differences
3142

3243
- **Execution Environment:** Jupyter Notebooks can be run locally on your machine or on a server, but Google Colab is hosted in the cloud.

0 commit comments

Comments
 (0)