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fix: Getting embeddings using text-embedding-005.
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lee1premium authored and iennae committed Oct 29, 2024
1 parent d56b312 commit 5bd0c38
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Showing 3 changed files with 4 additions and 4 deletions.
4 changes: 2 additions & 2 deletions ai-platform/snippets/embedding-model-tuning.js
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@ async function main(
project,
outputDir,
pipelineJobDisplayName = 'embedding-customization-pipeline-sample',
baseModelVersionId = 'text-embedding-004',
baseModelVersionId = 'text-embedding-005',
taskType = 'DEFAULT',
corpusPath = 'gs://cloud-samples-data/ai-platform/embedding/goog-10k-2024/r11/corpus.jsonl',
queriesPath = 'gs://cloud-samples-data/ai-platform/embedding/goog-10k-2024/r11/queries.jsonl',
Expand Down Expand Up @@ -62,7 +62,7 @@ async function main(
};
const pipelineJob = {
templateUri:
'https://us-kfp.pkg.dev/ml-pipeline/llm-text-embedding/tune-text-embedding-model/v1.1.3',
'https://us-kfp.pkg.dev/ml-pipeline/llm-text-embedding/tune-text-embedding-model/v1.1.4',
displayName: pipelineJobDisplayName,
runtimeConfig,
};
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2 changes: 1 addition & 1 deletion ai-platform/snippets/predict-text-embeddings-preview.js
Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@ async function main() {

// TODO(developer): Update the following for your own use case.
const project = 'long-door-651';
const model = 'text-embedding-preview-0815';
const model = 'text-embedding-005';
const location = 'us-central1';
// Calculate the embedding for code blocks. Using 'RETRIEVAL_DOCUMENT' for corpus.
// Specify the task type as 'CODE_RETRIEVAL_QUERY' for query, e.g. 'Retrieve a function that adds two numbers'.
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2 changes: 1 addition & 1 deletion ai-platform/snippets/predict-text-embeddings.js
Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@
// [START generativeaionvertexai_sdk_embedding]
async function main(
project,
model = 'text-embedding-004',
model = 'text-embedding-005',
texts = 'banana bread?;banana muffins?',
task = 'QUESTION_ANSWERING',
dimensionality = 0,
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