The evaluation in the model card was executed using this distilled model, not the original.
This model was trained in streaming mode over large precomputed feature shards with incremental PCA (384d), vocabulary quantization capped at 32k effective tokens, and fine-tuning optimizations for large-scale data.
from model2vec import StaticModel
model = StaticModel.from_pretrained("cnmoro/static-nomic-384-pten")
# Compute text embeddings
embeddings = model.encode(["Example sentence"])
Or using sentence-transformers library:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('cnmoro/static-nomic-384-pten')
# Compute text embeddings
embeddings = model.encode(["Example sentence"])
Runs of cnmoro static-nomic-384-pten on huggingface.co
520
Total runs
1
24-hour runs
-14
3-day runs
14
7-day runs
342
30-day runs
More Information About static-nomic-384-pten huggingface.co Model
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