coldra1n / snowflake_workshop Goto Github PK

Successfully completed BUILD LLM Bootcamp Day 1.

Get exclusive access to Snowpark Container Services - currently in Private Preview - by clicking on the link provided during the LLM Bootcamp session.

NOTE: If you are not able to get a SPCS user account, you can still attend sessions on Day 1 and Day 2 to earn the badge after completing the assessment by December 8, 2023 11:59PM Pacific Time.

Log into Snowflake account using your credentials -- https://app.snowflake.com/sfsenorthamerica/build_spcs

After you log into your Snowflake account, click on Worksheets on the left navigation menu and then click on '+' button on top right and select SQL Worksheet.

In the SQL Worksheet, run the following commands to select database, schema, and warehouse assigned to you:

use DB_USER####.SCHEMA_LLM;
use WAREHOUSE WH_XS_USER####;

NOTE: In the above SQL, replace #### in database name and warehouse with your user number.

Check the status of your compute pool by running the following command:

show compute pools;

NOTE: If the state of your compute pool is STARTING or RESIZING, wait a few mins until it's in IDLE or ACTIVE state before proceeding.

Drop service from Day 1 to free up resources for Day 2 by running the following commands:

show services;

Assuming you have successfully completed hands-on lab from Day 1, the above command will list service that was created when you deployed Llama 2 from Hugging Face in SPCS. If that's the case, run the following command to drop that service.

drop service SERVICE_ID_GOES_HERE;

NOTE: The service ID should like something like SERVICE_FD43C8AA84BD11EE8E7CE246F4FD5A27

Run the following command to create the service that will host the Jupyter Notebook which will be accessible via a public endpoint.

create service FINETUNE_LLM_SERVICE
  MIN_INSTANCES = 1
  MAX_INSTANCES = 1
  COMPUTE_POOL = COMPUTE_POOL_USER####
  SPEC = '@yaml_stage/llm-bootcamp.yaml';

NOTE: In the above SQL, replace #### in compute pool name with your user number.

Run the following command to check the status of FINETUNE_LLM_SERVICE service

select 
  v.value:containerName::varchar container_name
  ,v.value:status::varchar status  
  ,v.value:message::varchar message
from (select parse_json(system$get_service_status('FINETUNE_LLM_SERVICE'))) t, 
lateral flatten(input => t.$1) v;

NOTE: Make sure the Status is set to READY and Message is set to Running before proceeding.

Run the following command to access the endpoint where Jupyter Notebook is hosted in SPCS.

show endpoints in service FINETUNE_LLM_SERVICE;

In the Results section look for a column named ingress_url and copy the URL. It should look something similar to bab5b3y-sfsenorthamerica-build-spcs.snowflakecomputing.app

NOTE: Make sure the Status is set to READY and Message is set to Running before proceeding.

• Open a new browser window and paste the Jupyter Notebook service endpoint URL copied in step 7
• Login using your Snowflake credentials
• On the left hand side, double click on llm-day2-notebook.ipynb
• Follow instructions and run through each cell in the Notebook