Instructions to use fjavigv/snoweu_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fjavigv/snoweu_v2 with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("fjavigv/snoweu_v2")

sentences = [
    "What strategies can be implemented to effectively leverage private financing opportunities for small and medium-sized enterprises (SMEs)?",
    "(13) While the energy savings potential remains large in all sectors, there is a particular challenge relating to transport, as it is responsible for more than 30 % of final energy consumption, and to buildings, since 75 % of the Union’s building stock has a poor energy performance. Another increasingly important sector is the information and communications technology (ICT) sector, which is responsible for 5 to 9 % of the world’s total electricity use and more than 2 % of global emissions. In 2018, data centres accounted for 2,7 % of the electricity demand in the EU-28. In that context, the Commission, in its communication of 19 February 2020 on ‘Shaping Europe's digital future’ (the ‘Union’s Digital Strategy’), highlighted the need for highly energy-efficient and sustainable data centres and transparency measures for telecoms operators as regards their environmental footprint. Furthermore, the possible increase in industry’s energy demand that may result from its decarbonisation, particularly for energy intensive processes, should also be taken into account.",
    "SMEs in order to leverage and trigger private financing for SMEs.",
    "►M5 — ◄  K Gases (petroleum), refinery; Refinery gas (A complex combination obtained from various petroleum refining operations. It consists of hydrogen and hydrocarbons having carbon numbers predominantly in the range of C1 through C3.) 649-153-00-0 272-338-9 68814-67-5 ►M5 — ◄  K Gases (petroleum), platformer products separator off; Refinery gas (A complex combination obtained from the chemical reforming of naphthenes to aromatics. It consists of hydrogen and saturated aliphatic hydrocarbons having carbon numbers predominantly in the range of C2 through C4.) 649-154-00-6 272-343-6 68814-90-4 ►M5 — ◄  K Gases (petroleum), hydrotreated sour kerosine depentaniser stabiliser off; Refinery gas (The complex combination obtained from the"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
Google Colab
Kaggle

snoweu_v2

File size: 680 Bytes

35d9494

{
  "_name_or_path": "Snowflake/snowflake-arctic-embed-m-v1.5",
  "architectures": [
    "BertModel"
  ],
  "attention_probs_dropout_prob": 0.1,
  "classifier_dropout": null,
  "gradient_checkpointing": false,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0.1,
  "hidden_size": 768,
  "initializer_range": 0.02,
  "intermediate_size": 3072,
  "layer_norm_eps": 1e-12,
  "max_position_embeddings": 512,
  "model_type": "bert",
  "num_attention_heads": 12,
  "num_hidden_layers": 12,
  "pad_token_id": 0,
  "position_embedding_type": "absolute",
  "torch_dtype": "float32",
  "transformers_version": "4.48.1",
  "type_vocab_size": 2,
  "use_cache": true,
  "vocab_size": 30522
}