Examples¶
ESM model¶
1"""In this example we compute embedding and run masked inference
2 on the ESM2 language model."""
3
4from ginkgo_ai_client import (
5 GinkgoAIClient,
6 esm_mean_embedding_params,
7 esm_masked_inference_params,
8)
9
10client = GinkgoAIClient()
11
12# Simple query for embedding computation
13prediction = client.query(esm_mean_embedding_params("MLYLRRL"))
14# prediction["embedding"] == [1.05, -2.34, ...]
15
16
17# Simple query for masked inference
18prediction = client.query(esm_masked_inference_params("MLY<mask>RRL"))
19
20queries = [
21 esm_mean_embedding_params("MLYLRRL"),
22 esm_mean_embedding_params("MLYRRL"),
23 esm_mean_embedding_params("MLYLLRRL"),
24]
25predictions = client.batch_query(queries)
26
27# predictions[0]["result"]["embedding"] == [1.05, -2.34, ...]
AA0 model¶
1"""In this example we compute embedding and run masked inference
2 on the aa02 language model."""
3
4from ginkgo_ai_client import (
5 GinkgoAIClient,
6 aa0_mean_embedding_params,
7 aa0_masked_inference_params,
8)
9
10client = GinkgoAIClient()
11
12# Simple query for embedding computation
13prediction = client.query(aa0_mean_embedding_params("MLYLRRL"))
14# prediction["embedding"] == [1.05, -2.34, ...]
15
16
17# Simple query for masked inference
18prediction = client.query(aa0_masked_inference_params("MLY<mask>RRL"))
19
20queries = [
21 aa0_mean_embedding_params("MLYLRRL"),
22 aa0_mean_embedding_params("MLYRRL"),
23 aa0_mean_embedding_params("MLYLLRRL"),
24]
25predictions = client.batch_query(queries)
26
27# predictions[0]["result"]["embedding"] == [1.05, -2.34, ...]
3’UTR model¶
1"""In this example we compute embedding and run masked inference
2 on Ginkgo's 3'UTR language model."""
3
4from ginkgo_ai_client import (
5 GinkgoAIClient,
6 three_utr_mean_embedding_params,
7 three_utr_masked_inference_params,
8)
9
10client = GinkgoAIClient()
11
12# Simple query for embedding computation
13prediction = client.query(three_utr_mean_embedding_params("ATTGCG"))
14# prediction["embedding"] == [1.05, -2.34, ...]
15
16
17# Simple query for masked inference
18prediction = client.query(three_utr_masked_inference_params("ATT<mask>TAC"))
19
20queries = [
21 three_utr_mean_embedding_params("AGCGC"),
22 three_utr_mean_embedding_params("ATTGCG"),
23 three_utr_mean_embedding_params("TACCGCA"),
24]
25predictions = client.batch_query(queries)
26
27# predictions[0]["result"]["embedding"] == [1.05, -2.34, ...]