Leverage the LLama 3.2 Vision models with Snowflake Notebooks on Snowpark Container Services through Container Runtime. This quickstart will show you how you can:
This is possible by combining the latest vision language models with Snowpark Container Services, which gives you a flexible container infrastructure for supporting AI/ML workloads.
This Quickstart will guide you through the steps of running Snowflake Notebooks with Container Runtime. Once you have a GPU enabled runtime, you can then use the attached notebook to start using the Llama 3.2 Vision model using Transformers. Additionally, once you setup your container environment, this notebook will support using other Transformers models with some slight modifications.
Complete the following steps to setup your account:
USE ROLE accountadmin;
CREATE OR REPLACE DATABASE container_runtime_lab;
CREATE SCHEMA notebooks;
CREATE OR REPLACE ROLE container_runtime_lab_user;
GRANT ROLE container_runtime_lab_user to USER <YOUR_USER>;
GRANT USAGE ON DATABASE container_runtime_lab TO ROLE container_runtime_lab_user;
GRANT ALL ON SCHEMA container_runtime_lab.notebooks TO ROLE container_runtime_lab_user;
GRANT CREATE STAGE ON SCHEMA container_runtime_lab.notebooks TO ROLE container_runtime_lab_user;
GRANT CREATE NOTEBOOK ON SCHEMA container_runtime_lab.notebooks TO ROLE container_runtime_lab_user;
GRANT CREATE SERVICE ON SCHEMA container_runtime_lab.notebooks TO ROLE container_runtime_lab_user;
CREATE OR REPLACE WAREHOUSE CONTAINER_RUNTIME_WH AUTO_SUSPEND = 60;
GRANT ALL ON WAREHOUSE CONTAINER_RUNTIME_WH TO ROLE container_runtime_lab_user;
-- Create and grant access to compute pools
-- If you get errors about limits, reduce the number of nodes in the compute pools
CREATE COMPUTE POOL IF NOT EXISTS gpu_nv_m_nodes
MIN_NODES = 1
MAX_NODES = 3
INSTANCE_FAMILY = GPU_NV_M;
GRANT USAGE ON COMPUTE POOL gpu_nv_m_nodes TO ROLE container_runtime_lab_user;
-- Create and grant access to EAIs
-- Substep #1: create network rules (these are schema-level objects; end users do not need direct access to the network rules)
create network rule allow_all_rule
TYPE = 'HOST_PORT'
MODE= 'EGRESS'
VALUE_LIST = ('0.0.0.0:443','0.0.0.0:80');
-- Substep #2: create external access integration (these are account-level objects; end users need access to this to access the public internet with endpoints defined in network rules)
CREATE OR REPLACE EXTERNAL ACCESS INTEGRATION allow_all_integration
ALLOWED_NETWORK_RULES = (allow_all_rule)
ENABLED = true;
CREATE OR REPLACE NETWORK RULE pypi_network_rule
MODE = EGRESS
TYPE = HOST_PORT
VALUE_LIST = ('pypi.org', 'pypi.python.org', 'pythonhosted.org', 'files.pythonhosted.org');
CREATE OR REPLACE EXTERNAL ACCESS INTEGRATION pypi_access_integration
ALLOWED_NETWORK_RULES = (pypi_network_rule)
ENABLED = true;
CREATE OR REPLACE NETWORK RULE HF_NETWORK_RULE
MODE = EGRESS
TYPE = HOST_PORT
VALUE_LIST = ('huggingface.co', 'cdn-lfs.huggingface.co','cdn-lfs-us-1.huggingface.co', 'cdn-lfs-us-1.hf.co');
CREATE EXTERNAL ACCESS INTEGRATION hf_access_integration
ALLOWED_NETWORK_RULES = (HF_NETWORK_RULE)
ENABLED = true;
GRANT USAGE ON INTEGRATION allow_all_integration TO ROLE container_runtime_lab_user;
GRANT USAGE ON INTEGRATION pypi_access_integration TO ROLE container_runtime_lab_user;
GRANT USAGE ON INTEGRATION hf_access_integration TO ROLE container_runtime_lab_user;