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-v2")
# 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-v2')
# Compute text embeddings
embeddings = model.encode(["Example sentence"])
Runs of cnmoro static-nomic-384-pten-v2 on huggingface.co
84
Total runs
-3
24-hour runs
-4
3-day runs
8
7-day runs
-9
30-day runs
More Information About static-nomic-384-pten-v2 huggingface.co Model
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static-nomic-384-pten-v2 is an open source model from GitHub that offers a free installation service, and any user can find static-nomic-384-pten-v2 on GitHub to install. At the same time, huggingface.co provides the effect of static-nomic-384-pten-v2 install, users can directly use static-nomic-384-pten-v2 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
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