Instructions to use NilsML/MNLP_M3_document_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NilsML/MNLP_M3_document_encoder with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("NilsML/MNLP_M3_document_encoder")

sentences = [
    "Electromagnetic radiation behaves like particles as well as what?",
    "quantum metrology allows us to attain a measurement precision that surpasses the classically achievable limit by using quantum characters. the metrology precision is raised from the standard quantum limit ( sql ) to the heisenberg limit ( hl ) by using entanglement. however, it was reported that the hl returns to the sql in the presence of local dephasing environments under the long encoding - time condition. we evaluate here the exact impacts of local dissipative environments on quantum metrology, based on the ramsey interferometer. it is found that the hl is asymptotically recovered under the long encoding - time condition for a finite number of the probe atoms. our analysis reveals that this is essentially due to the formation of a bound state between each atom and its environment. this provides an avenue for experimentation to implement quantum metrology under practical conditions via engineering of the formation of the system - environment bound state.",
    "plasmons in two - dimensional electron systems with nonparabolic bands, such as graphene, feature strong dependence on electron - electron interactions. we use a many - body approach to relate plasmon dispersion at long wavelengths to landau fermi - liquid interactions and quasiparticle velocity. an identical renormalization is shown to arise for the magnetoplasmon resonance. for a model with n > > 1 fermion species, this approach predicts a power - law dependence for plasmon frequency vs. carrier concentration, valid in a wide range of doping densities, both high and low. gate tunability of plasmons in graphene can be exploited to directly probe the effects of electron - electron interaction.",
    "the study of earth - mass extrasolar planets via the radial - velocity technique and the measurement of the potential cosmological variability of fundamental constants call for very - high - precision spectroscopy at the level of $ \\ updelta \\ lambda / \\ lambda < 10 ^ { - 9 } $. wavelength accuracy is obtained by providing two fundamental ingredients : 1 ) an absolute and information - rich wavelength source and 2 ) the ability of the spectrograph and its data reduction of transferring the reference scale ( wavelengths ) to a measurement scale ( detector pixels ) in a repeatable manner. the goal of this work is to improve the wavelength calibration accuracy of the harps spectrograph by combining the absolute spectral reference provided by the emission lines of a thorium - argon hollow - cathode lamp ( hcl ) with the spectrally rich and precise spectral information of a fabry - p \\ ' erot - based calibration source. on the basis of calibration frames acquired each night since the fabry - p \\ ' erot etalon was installed on harps in 2011, we construct a combined wavelength solution which fits simultaneously the thorium emission lines and the fabry - p \\ ' erot lines. the combined fit is anchored to the absolute thorium wavelengths, which provide the ` zero - point ' of the spectrograph, while the fabry - p \\ ' erot lines are used to improve the ( spectrally ) local precision. the obtained wavelength solution is verified for auto - consistency and tested against a solution obtained using the harps laser - frequency comb ( lfc ). the combined thorium + fabry - p \\ ' erot wavelength solution shows significantly better performances compared to the thorium - only calibration. the presented techniques will therefore be used in the new harps and harps - n pipeline, and will be exported to the espresso spectrograph."
]
embeddings = model.encode(sentences)

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

Notebooks
Google Colab
Kaggle

MNLP_M3_document_encoder / model.safetensors

NilsML

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