--- tags: - sentence-transformers - sentence-similarity - feature-extraction - dense - generated_from_trainer - dataset_size:35100 - loss:SoftmaxLoss base_model: AI-Growth-Lab/PatentSBERTa widget: - source_sentence: '1. A multi-modal monitor system to obtain quantitative, coordinated measurement of emissions from a turbine having at least one of a blade and a rotor, comprising: a first sensor for measuring at least one type of emission generated by the turbine during movement of the at least one of the blade and the rotor and generating a first emission signal; a second sensor for measuring a different type of emission generated by the turbine and generating a second emission signal; a third sensor for measuring a different type of emission than that measured by the first and second sensors; a data storage unit capable of storing emission signals over time; and a housing containing at least the first, second and third sensors and capable of being placed operationally at a distance from the turbine in an outdoor location to be monitored; wherein each of the first, second, and third sensors measures one type of emission selected from mechanical wave, optical radiation, electrical, vibration, audible sound, and infrasound.' sentences: - '1. An in-wheel motor installed inside a wheel disk of a wheel to rotationally drive the wheel around a shaft of the wheel by way of applying a current thereto, the in-wheel motor comprising: a coreless cylindrical coil body to which a lead wire for applying a current is connected, the shaft being inserted in an inner circumferential side of the coil body, the coil body supported at one end by a coil body support member that is fixed to the shaft; a cylindrical outer yoke that is disposed on an outer circumferential side of the coil body, and is fixed to the wheel disk; a magnet that is fixed on an inner circumferential face of the outer yoke, an inner surface of the magnet disposed proximate an outer circumferential face of the coil body; a cylindrical inner yoke having an outer circumferential face disposed proximate to an inner circumferential face of the coil body, the inner yoke being fixed to the outer yoke and being rotatable around the shaft; a brake disk that is fixed to an inner circumferential side of the inner yoke; and a caliper that is provided on the inner circumferential side of the inner yoke to brake the brake disk.' - '1. A multi-modal monitor system to obtain quantitative, coordinated measurement of emissions from a turbine having at least one of a blade and a rotor, comprising: a first sensor for measuring at least one type of emission generated by the turbine during movement of the at least one of the blade and the rotor and generating a first emission signal; a second sensor for measuring a different type of emission generated by the turbine and generating a second emission signal; a third sensor for measuring a different type of emission than that measured by the first and second sensors; a data storage unit capable of storing emission signals over time; and a housing containing at least the first, second and third sensors and capable of being placed operationally at a distance from the turbine in an outdoor location to be monitored; wherein each of the first, second, and third sensors measures one type of emission selected from mechanical wave, optical radiation, electrical, vibration, audible sound, and infrasound.' - 1. An identification medium comprising a cholesteric liquid crystal layer on which a hologram is formed, a first supporting member and a second supporting member between which the cholesteric liquid crystal layer is sandwiched, and at least one thereof is made of transparent material which does not disturb circularly polarized light reflected from the cholesteric liquid crystal layer, and a mounting region to be sewn onto an object, the first supporting member and the second supporting member extending to the mounting region and being adhered directly to each other by an adhesive layer in the mounting region, wherein the first supporting member is a polyurethane film or a cloth, and the cholesteric liquid crystal layer is affixed to both of the first supporting member and the second supporting member by adhesive layers. - source_sentence: '1. A process of making light olefins, in a combined Oxygenate to Olefin (XTO)-Olefin Cracking (OC) process, from an oxygen-containing, halogenide-containing or sulphur-containing organic feedstock comprising: selecting a molecular sieve having pores of 10- or more-membered rings, wherein the molecular sieve is a zeolite; contacting the molecular sieve with a metal silicate, different from said molecular sieve, comprising at least one alkaline earth metal to form a catalyst composite, wherein the catalyst composite comprises at least 10 wt % of the zeolite and at least 0.1 wt % of silicate based on a total weight of the catalyst composite; providing a first portion and a second portion of a feedstock that is an oxygen-containing, halogenide-containing, or sulphur-containing organic feedstock; providing an XTO reaction zone, an OC reaction zone and a catalyst regeneration zone, wherein one or more catalysts are in the XTO reaction zone and the same one or more catalysts are in the OC reaction zone, wherein at least one of the one or more catalysts is the catalyst composite; wherein the one or more catalysts circulate in the three zones, such that at least a portion of the one or more catalysts from the catalyst regeneration zone is passed to the OC reaction zone, at least a portion of the one or more catalysts in the OC reaction zone is passed to the XTO reaction zone and at least a portion of the one or more catalysts in the XTO reaction zone is passed to the catalyst regeneration zone; contacting the first portion of the feedstock in the XTO reactor with the one or more catalysts at conditions effective to convert at least a portion of the feedstock to form an XTO reactor effluent comprising light olefins and a heavy hydrocarbon fraction; separating the light olefins from the heavy hydrocarbon fraction; and contacting the heavy hydrocarbon fraction and the second portion of the feedstock in the OC reactor with the one or more catalysts at conditions effective to convert at least a portion of the heavy hydrocarbon fraction and the feedstock to light olefins.' sentences: - '1. A process of making light olefins, in a combined Oxygenate to Olefin (XTO)-Olefin Cracking (OC) process, from an oxygen-containing, halogenide-containing or sulphur-containing organic feedstock comprising: selecting a molecular sieve having pores of 10- or more-membered rings, wherein the molecular sieve is a zeolite; contacting the molecular sieve with a metal silicate, different from said molecular sieve, comprising at least one alkaline earth metal to form a catalyst composite, wherein the catalyst composite comprises at least 10 wt % of the zeolite and at least 0.1 wt % of silicate based on a total weight of the catalyst composite; providing a first portion and a second portion of a feedstock that is an oxygen-containing, halogenide-containing, or sulphur-containing organic feedstock; providing an XTO reaction zone, an OC reaction zone and a catalyst regeneration zone, wherein one or more catalysts are in the XTO reaction zone and the same one or more catalysts are in the OC reaction zone, wherein at least one of the one or more catalysts is the catalyst composite; wherein the one or more catalysts circulate in the three zones, such that at least a portion of the one or more catalysts from the catalyst regeneration zone is passed to the OC reaction zone, at least a portion of the one or more catalysts in the OC reaction zone is passed to the XTO reaction zone and at least a portion of the one or more catalysts in the XTO reaction zone is passed to the catalyst regeneration zone; contacting the first portion of the feedstock in the XTO reactor with the one or more catalysts at conditions effective to convert at least a portion of the feedstock to form an XTO reactor effluent comprising light olefins and a heavy hydrocarbon fraction; separating the light olefins from the heavy hydrocarbon fraction; and contacting the heavy hydrocarbon fraction and the second portion of the feedstock in the OC reactor with the one or more catalysts at conditions effective to convert at least a portion of the heavy hydrocarbon fraction and the feedstock to light olefins.' - '1. A needle assembly system comprising: a needle assembly including a needle and a needle support; a cover including a distal portion adapted to house at least a distal end of the needle and a proximal portion adapted to house the needle support, wherein the proximal portion includes a first portion and a second portion, wherein the first portion has a first inner diameter substantially equal to an outer diameter of the needle support such that the first portion of the proximal portion of the cover is frictionally engaged with the needle support in a first position and the second portion has a second inner diameter greater than the diameter of the needle support such that there is radial separation between the cover and the needle support in a second position, wherein the second portion of the proximal portion has a length greater than or equal to a length of the needle support, wherein the needle support is configured to be axially advanced from the first position to the second position such that a proximal end of the needle assembly does not extend past a proximal end of the cover.' - '1. A membrane electrode assembly for a polymer electrolyte fuel cell, comprising: an electrolyte membrane; a catalyst layer; a conductive porous gas diffusion layer, wherein the catalyst layer and the electrolyte membrane have common boundaries; and grooves for allowing one of passage and retention of a fluid being formed in the common boundaries, and wherein the grooves have a tapered shape such that a width of each groove is largest at the common boundary, and wherein the catalyst layer is disposed between the gas diffusion layer and the electrolyte membrane.' - source_sentence: '1. A computer hardware-implemented method of preventing a cascading failure in a complex stream computer system, wherein a cascading failure results in an untrustworthy output from the complex stream computer system, and wherein the computer hardware-implemented method comprises: receiving a first set of binary data that identifies multiple subcomponents in a complex stream computer system, wherein the identified multiple subcomponents comprise multiple upstream subcomponents and a downstream subcomponent, and wherein the multiple upstream subcomponents execute upstream computational processes; receiving a second set of binary data that identifies multiple outputs generated by the multiple upstream subcomponents; receiving a third set of binary data that identifies multiple inputs to the downstream subcomponent, wherein the identified multiple inputs to the downstream subcomponent are the identified multiple outputs generated by the multiple upstream subcomponents, and wherein the identified multiple inputs are inputs to a downstream computational process that is executed by the downstream subcomponent; examining, by computer hardware, each of the upstream computational processes to determine an accuracy of each of the identified multiple outputs based upon: generating, by computer hardware, accuracy values by assigning a determined accuracy value to each of the identified multiple outputs, wherein the determined accuracy value describes a confidence level of an accuracy of each of the identified multiple outputs, and wherein each of the identified multiple outputs are created by a separate upstream computational process in separate upstream subcomponents from the multiple upstream subcomponents; generating, by the computer hardware, weighting values by assigning a weighting value to each of the identified multiple inputs to the downstream subcomponent, wherein the weighting value describes a criticality level of each of the identified multiple inputs when executing the downstream computational process in the downstream subcomponent; and utilizing, by the computer hardware, the determined accuracy values and the weighting values to dynamically adjust which of the identified multiple inputs are used by the downstream subcomponent until an output from the downstream subcomponent meets a predefined trustworthiness level, wherein a trustworthiness of the output from the downstream subcomponent is based on the determined accuracy value of each of the identified multiple outputs and the weighting value of each of the identified multiple inputs to the downstream subcomponent.' sentences: - '1. A method comprising: encoding, by a processing module of a computing device, a data segment of a data object into a set of encoded data slices; determining, by the processing module, storage requirements of the data object; determining, by the processing module, memory device capabilities of a plurality of distributed storage units based on types of memory devices, wherein at least one of the distributed storage units of the plurality of distributed storage units includes multiple types of memory devices, and wherein a first type of memory device has first memory characteristics and a second type of memory device has second memory characteristics; determining, by the processing module, a storage mode based on one or more of the storage requirements of the data object, the memory device capabilities of a dispersed storage network (DSN) memory, and a type of data, the storage mode including a time phase indicator specifying one or more time intervals for a given set of storage requirements; identifying, by the processing module, a set of distributed storage units of the plurality of distributed storage units that have at least one or more of the multiple types of memory devices based on the storage mode; and sending, by the computing device, at least a write threshold number of encoded data slices of the data segment to the set of distributed storage units for storage in the at least one or more of the multiple types of memory devices in accordance with the storage mode, wherein the write threshold number is greater than a decode threshold number and less than a total number, wherein the decode threshold number corresponds to a minimum number of encoded data slices of the set of encoded data slices that is needed to recover the data segment, wherein the total number corresponds to a number of encoded data slices in the set of encoded data slices.' - '1. A chemical looping combustion apparatus for solid fuels using different oxygen carriers, comprising: a solid fuel chemical looping combustor configured to receive solid fuels and to produce carbon dioxide and steam by combustion of the solid fuels; a gaseous fuel chemical looping combustor configured to receive gaseous fuels and to produce carbon dioxide and steam by combustion of the gaseous fuels; and a devolatilization reactor configured to produce solids and gases by devolatilizing the solid fuels, wherein the solid fuels received by the solid fuel chemical looping combustor and the gaseous fuels received by the gaseous fuel chemical looping combustor are the solids and the gases produced by the devolatilization reactor, respectively, wherein the solid fuel chemical looping combustor comprises: an oxidation reactor; a loop seal configured to receive a metallic oxide from the oxidation reactor; a reduction reactor configured to cause the solid fuels flowing from the devolatilization reactor and the metallic oxide transferred from the loop seal to react with each other, thereby reducing the oxygen carriers; a downcomer connected to an outlet of the loop seal and extending to a lower portion of the reduction reactor to receive the solid fuels, wherein the oxygen carriers reduced in the reduction reactor are provided to the oxidation reactor such that the oxygen carriers are re-circulated, and wherein the solid fuels are introduced into the reduction reactor from a middle point of a longitudinal length of the downcomer.' - '1. A computer hardware-implemented method of preventing a cascading failure in a complex stream computer system, wherein a cascading failure results in an untrustworthy output from the complex stream computer system, and wherein the computer hardware-implemented method comprises: receiving a first set of binary data that identifies multiple subcomponents in a complex stream computer system, wherein the identified multiple subcomponents comprise multiple upstream subcomponents and a downstream subcomponent, and wherein the multiple upstream subcomponents execute upstream computational processes; receiving a second set of binary data that identifies multiple outputs generated by the multiple upstream subcomponents; receiving a third set of binary data that identifies multiple inputs to the downstream subcomponent, wherein the identified multiple inputs to the downstream subcomponent are the identified multiple outputs generated by the multiple upstream subcomponents, and wherein the identified multiple inputs are inputs to a downstream computational process that is executed by the downstream subcomponent; examining, by computer hardware, each of the upstream computational processes to determine an accuracy of each of the identified multiple outputs based upon: generating, by computer hardware, accuracy values by assigning a determined accuracy value to each of the identified multiple outputs, wherein the determined accuracy value describes a confidence level of an accuracy of each of the identified multiple outputs, and wherein each of the identified multiple outputs are created by a separate upstream computational process in separate upstream subcomponents from the multiple upstream subcomponents; generating, by the computer hardware, weighting values by assigning a weighting value to each of the identified multiple inputs to the downstream subcomponent, wherein the weighting value describes a criticality level of each of the identified multiple inputs when executing the downstream computational process in the downstream subcomponent; and utilizing, by the computer hardware, the determined accuracy values and the weighting values to dynamically adjust which of the identified multiple inputs are used by the downstream subcomponent until an output from the downstream subcomponent meets a predefined trustworthiness level, wherein a trustworthiness of the output from the downstream subcomponent is based on the determined accuracy value of each of the identified multiple outputs and the weighting value of each of the identified multiple inputs to the downstream subcomponent.' - source_sentence: '1. A method comprising the steps of: (a) providing one or more tissues, cell types, or a lysate thereof, obtained from a patient administered at least one dose of a compound of formula I:  or a pharmaceutically acceptable salt thereof, wherein: Ring A is selected from: Ring A is an optionally substituted group selected from phenyl, an 8-10 membered bicyclic partially unsaturated or aryl ring, a 5-6 membered monocyclic heteroaryl ring having 1-4 heteroatoms independently selected from nitrogen, oxygen, or sulfur, or an 8-10 membered bicyclic heteroaryl ring having 1-5 heteroatoms independently selected from nitrogen, oxygen, or sulfur; Ring B is phenyl, a 5-6 membered heteroaryl ring having 1-3 heteroatoms independently selected from N, O or S, a 5-6 membered saturated heterocyclic ring having 1-2 heteroatoms independently selected from N, O or S, or an 8-10 membered bicyclic partially unsaturated or aryl ring having 1-3 heteroatoms independently selected from N, O or S; R R L is a bivalent C L is a bivalent C L is a bivalent C L is a bivalent C L is a bivalent C Y is hydrogen, C L is a bivalent C Y is C L is a covalent bond and Y is selected from: L is —C(O)— and Y is selected from: L is —N(R)C(O)— and Y is selected from: L is a bivalent C L is —CH each R R W is a bivalent C R m is 0, 1, 2, 3 or 4; each R (b) contacting said tissue, cell type, or a lysate thereof, with a compound of formula I, tethered to a detectable moiety to form a probe compound, wherein at least one protein kinase present in said tissue, cell type, or a lysate thereof, is covalently modified and the detectable moiety is selected from the group consisting of a fluorescent label, mass-tag, chemiluminescent group, chromophore, electron dense group, or an energy transfer agent; and (c) measuring the amount of said protein kinase covalently modified by the probe compound thereby to determine occupancy of said protein kinase by said compound of formula I as compared to occupancy of said protein kinase by said probe compound.' sentences: - '1. A detection circuit that is connectable to a magnetic sensor in which a first sensor unit and a second sensor unit are arranged at a predetermined angle with respect to each other, each sensor unit having a bridge circuit of magnetoresistance elements, the detection circuit comprising: a first comparison circuit including: a second comparison circuit including: a rotation angle calculation circuit that calculates a rotation angle of a magnetic field based on one of the comparison results of the first comparison circuit and a comparison result of the second comparison circuit, the rotation angle calculation circuit including a logic circuit that generates a third detection signal based on a comparison result of the third comparator and a comparison result of the fourth comparator.' - '1. A method comprising the steps of: (a) providing one or more tissues, cell types, or a lysate thereof, obtained from a patient administered at least one dose of a compound of formula I:  or a pharmaceutically acceptable salt thereof, wherein: Ring A is selected from: Ring A is an optionally substituted group selected from phenyl, an 8-10 membered bicyclic partially unsaturated or aryl ring, a 5-6 membered monocyclic heteroaryl ring having 1-4 heteroatoms independently selected from nitrogen, oxygen, or sulfur, or an 8-10 membered bicyclic heteroaryl ring having 1-5 heteroatoms independently selected from nitrogen, oxygen, or sulfur; Ring B is phenyl, a 5-6 membered heteroaryl ring having 1-3 heteroatoms independently selected from N, O or S, a 5-6 membered saturated heterocyclic ring having 1-2 heteroatoms independently selected from N, O or S, or an 8-10 membered bicyclic partially unsaturated or aryl ring having 1-3 heteroatoms independently selected from N, O or S; R R L is a bivalent C L is a bivalent C L is a bivalent C L is a bivalent C L is a bivalent C Y is hydrogen, C L is a bivalent C Y is C L is a covalent bond and Y is selected from: L is —C(O)— and Y is selected from: L is —N(R)C(O)— and Y is selected from: L is a bivalent C L is —CH each R R W is a bivalent C R m is 0, 1, 2, 3 or 4; each R (b) contacting said tissue, cell type, or a lysate thereof, with a compound of formula I, tethered to a detectable moiety to form a probe compound, wherein at least one protein kinase present in said tissue, cell type, or a lysate thereof, is covalently modified and the detectable moiety is selected from the group consisting of a fluorescent label, mass-tag, chemiluminescent group, chromophore, electron dense group, or an energy transfer agent; and (c) measuring the amount of said protein kinase covalently modified by the probe compound thereby to determine occupancy of said protein kinase by said compound of formula I as compared to occupancy of said protein kinase by said probe compound.' - 1. A method of treating lupus in a mammal, the method comprising administering to the mammal an antibody which binds an interleukin 3 receptor α (IL-3Rα) chain and which kills a plasmacytoid dendritic cell (pDC) or basophil to which it binds to thereby treat lupus in the mammal, wherein the antibody comprises the variable regions of antibody 7G3 or is a humanized form of antibody 7G3, and wherein the antibody is not conjugated to a toxic compound that kills a cell to which the antibody binds, and wherein the antibody is capable of inducing an enhanced level of effector function, and wherein the effector function is antibody-dependent cell cytotoxicity (ADCC) and/or antibody-dependent cell mediated phagocytosis (ADCP). - source_sentence: 1. A sputtering target having a component composition that contains 1 to 40 at % of Ga, 0.05 to 2 at % of Na as metal element components, and the balance composed of Cu and unavoidable impurities, wherein the sputtering target contains Na in at least one form selected from among sodium fluoride, sodium sulfide, and sodium selenide and the content of oxygen is from 100 to 1,000 ppm. sentences: - '1. An insulation bobbin unit of a stator, comprising: a first insulation bobbin having a first body and a plurality of first extension members coupled with the first body, wherein the first body has a first assembly hole, each of the extension members has a first wound portion, the first wound portion has a first top plate and one first side wall located on one side of the first top plate, and a thickness of the first top plate is smaller than that of the first side wall; and a second insulation bobbin having a second body and a plurality of second extension members, wherein the second body is coupled with the first body and has a second assembly hole aligning and communicating with the first assembly hole, the second extension members are coupled with the second body and aligned with the first extension members, each of the second extension members has a second wound portion, the second wound portion has a second top plate and one second side wall located on one side of the second top plate, and a room is defined by the first top plate, the first side wall, the second top plate and the second side wall, wherein the first side wall is aligned with one edge of the second top plate that is not mounted with the second side wall, and the second side wall is aligned with one edge of the first top plate that is not mounted with the first side wall.' - 1. A sputtering target having a component composition that contains 1 to 40 at % of Ga, 0.05 to 2 at % of Na as metal element components, and the balance composed of Cu and unavoidable impurities, wherein the sputtering target contains Na in at least one form selected from among sodium fluoride, sodium sulfide, and sodium selenide and the content of oxygen is from 100 to 1,000 ppm. - '1. An electrical energy supply system providing voltage to a first load, comprising: an external power group providing an external voltage; and a DC supply device receiving the external voltage and comprising: a first bus receiving the external voltage and coupled to the first load; a first converting unit converting the external voltage into a first converted voltage when a voltage level of the first bus reaches a pre-determined level, and converting a first stored voltage to generate a converted result when the voltage level of the first bus is less than the pre-determined level; a first storage unit storing the first converted voltage when the voltage level of the first bus reaches the pre-determined level and providing the first stored voltage to the first converting unit when the voltage level of the first bus is less than the pre-determined level; and a first smart energy management system (SEMS) controlling at least one of the first converting unit, the external power group and the first load according to at least one of the external voltage, a voltage level of the first bus and a voltage level of the first storage unit, wherein the first SEMS controls the external power group to adjust the external voltage according to the voltage level of the first bus.' pipeline_tag: sentence-similarity library_name: sentence-transformers --- # SentenceTransformer based on AI-Growth-Lab/PatentSBERTa This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [AI-Growth-Lab/PatentSBERTa](https://huggingface.co/AI-Growth-Lab/PatentSBERTa). It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. ## Model Details ### Model Description - **Model Type:** Sentence Transformer - **Base model:** [AI-Growth-Lab/PatentSBERTa](https://huggingface.co/AI-Growth-Lab/PatentSBERTa) - **Maximum Sequence Length:** 512 tokens - **Output Dimensionality:** 768 dimensions - **Similarity Function:** Cosine Similarity ### Model Sources - **Documentation:** [Sentence Transformers Documentation](https://sbert.net) - **Repository:** [Sentence Transformers on GitHub](https://github.com/huggingface/sentence-transformers) - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) ### Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False, 'architecture': 'MPNetModel'}) (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) ) ``` ## Usage ### Direct Usage (Sentence Transformers) First install the Sentence Transformers library: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python from sentence_transformers import SentenceTransformer # Download from the 🤗 Hub model = SentenceTransformer("sentence_transformers_model_id") # Run inference sentences = [ '1. A sputtering target having a component composition that contains 1 to 40 at % of Ga, 0.05 to 2 at % of Na as metal element components, and the balance composed of Cu and unavoidable impurities, wherein the sputtering target contains Na in at least one form selected from among sodium fluoride, sodium sulfide, and sodium selenide and the content of oxygen is from 100 to 1,000 ppm.', '1. A sputtering target having a component composition that contains 1 to 40 at % of Ga, 0.05 to 2 at % of Na as metal element components, and the balance composed of Cu and unavoidable impurities, wherein the sputtering target contains Na in at least one form selected from among sodium fluoride, sodium sulfide, and sodium selenide and the content of oxygen is from 100 to 1,000 ppm.', '1. An electrical energy supply system providing voltage to a first load, comprising: an external power group providing an external voltage; and a DC supply device receiving the external voltage and comprising: a first bus receiving the external voltage and coupled to the first load; a first converting unit converting the external voltage into a first converted voltage when a voltage level of the first bus reaches a pre-determined level, and converting a first stored voltage to generate a converted result when the voltage level of the first bus is less than the pre-determined level; a first storage unit storing the first converted voltage when the voltage level of the first bus reaches the pre-determined level and providing the first stored voltage to the first converting unit when the voltage level of the first bus is less than the pre-determined level; and a first smart energy management system (SEMS) controlling at least one of the first converting unit, the external power group and the first load according to at least one of the external voltage, a voltage level of the first bus and a voltage level of the first storage unit, wherein the first SEMS controls the external power group to adjust the external voltage according to the voltage level of the first bus.', ] embeddings = model.encode(sentences) print(embeddings.shape) # [3, 768] # Get the similarity scores for the embeddings similarities = model.similarity(embeddings, embeddings) print(similarities) # tensor([[1.0000, 1.0000, 0.0550], # [1.0000, 1.0000, 0.0550], # [0.0550, 0.0550, 1.0000]]) ``` ## Training Details ### Training Dataset #### Unnamed Dataset * Size: 35,100 training samples * Columns: sentence_0, sentence_1, and label * Approximate statistics based on the first 1000 samples: | | sentence_0 | sentence_1 | label | |:--------|:-------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------|:------------------------------------------------| | type | string | string | int | | details | | | | * Samples: | sentence_0 | sentence_1 | label | |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------| | 1. A method for producing float glass, comprising: feeding air to a first ion transport membrane which produces a stream of pure oxygen and a stream of oxygen-depleted air; feeding the stream of pure oxygen to a glass melting furnace; feeding a mixture of steam and a hydrocarbon fuel to one side of a second ion transport membrane and the stream of oxygen-depleted air to the other side of the second oxygen transport membrane to produce a stream of syngas and a nitrogen-rich stream; feeding the stream of syngas to a third ion transport membrane to produce a stream of pure hydrogen and a stream of hydrogen-depleted syngas; feeding the nitrogen-rich stream the hydrogen-depleted syngas stream to a combustor to produce an oxygen-free stream of nitrogen and carbon dioxide; removing H mixing the stream of pure hydrogen and the purified stream of nitrogen and carbon dioxide; and feeding the mixed stream to the surface of a float glass bath downstream of the glass melting furnace. | 1. A method for producing float glass, comprising: feeding air to a first ion transport membrane which produces a stream of pure oxygen and a stream of oxygen-depleted air; feeding the stream of pure oxygen to a glass melting furnace; feeding a mixture of steam and a hydrocarbon fuel to one side of a second ion transport membrane and the stream of oxygen-depleted air to the other side of the second oxygen transport membrane to produce a stream of syngas and a nitrogen-rich stream; feeding the stream of syngas to a third ion transport membrane to produce a stream of pure hydrogen and a stream of hydrogen-depleted syngas; feeding the nitrogen-rich stream the hydrogen-depleted syngas stream to a combustor to produce an oxygen-free stream of nitrogen and carbon dioxide; removing H mixing the stream of pure hydrogen and the purified stream of nitrogen and carbon dioxide; and feeding the mixed stream to the surface of a float glass bath downstream of the glass melting furnace. | 1 | | 1. An application device for a cosmetic product comprising: a holding member, an application member having a surface for application of the product, and a heating electric element; wherein the heating electric element is formed of at least one resistor mounted on a printed circuit positioned, at least in part at a distal end of the application member, and in that a surface area of the orthogonal projection of the resistor on a plane defined by the printed circuit is less than or equal to 10 mm | 1. An application device for a cosmetic product comprising: a holding member, an application member having a surface for application of the product, and a heating electric element; wherein the heating electric element is formed of at least one resistor mounted on a printed circuit positioned, at least in part at a distal end of the application member, and in that a surface area of the orthogonal projection of the resistor on a plane defined by the printed circuit is less than or equal to 10 mm | 0 | | 1. A vehicle communication network comprises: a plurality of vehicle control modules; a network fabric, wherein the network fabric comprises: a network manager operably coupled to the network fabric, wherein the network manager is operable to: wherein the data bridge is operable to: | 1. A vehicle communication network comprises: a plurality of vehicle control modules; a network fabric, wherein the network fabric comprises: a network manager operably coupled to the network fabric, wherein the network manager is operable to: wherein the data bridge is operable to: | 1 | * Loss: [SoftmaxLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#softmaxloss) ### Training Hyperparameters #### Non-Default Hyperparameters - `per_device_train_batch_size`: 16 - `per_device_eval_batch_size`: 16 - `num_train_epochs`: 1 - `multi_dataset_batch_sampler`: round_robin #### All Hyperparameters
Click to expand - `do_predict`: False - `eval_strategy`: no - `prediction_loss_only`: True - `per_device_train_batch_size`: 16 - `per_device_eval_batch_size`: 16 - `gradient_accumulation_steps`: 1 - `eval_accumulation_steps`: None - `torch_empty_cache_steps`: None - `learning_rate`: 5e-05 - `weight_decay`: 0.0 - `adam_beta1`: 0.9 - `adam_beta2`: 0.999 - `adam_epsilon`: 1e-08 - `max_grad_norm`: 1 - `num_train_epochs`: 1 - `max_steps`: -1 - `lr_scheduler_type`: linear - `lr_scheduler_kwargs`: None - `warmup_ratio`: None - `warmup_steps`: 0 - `log_level`: passive - `log_level_replica`: warning - `log_on_each_node`: True - `logging_nan_inf_filter`: True - `enable_jit_checkpoint`: False - `save_on_each_node`: False - `save_only_model`: False - `restore_callback_states_from_checkpoint`: False - `use_cpu`: False - `seed`: 42 - `data_seed`: None - `bf16`: False - `fp16`: False - `bf16_full_eval`: False - `fp16_full_eval`: False - `tf32`: None - `local_rank`: -1 - `ddp_backend`: None - `debug`: [] - `dataloader_drop_last`: False - `dataloader_num_workers`: 0 - `dataloader_prefetch_factor`: None - `disable_tqdm`: False - `remove_unused_columns`: True - `label_names`: None - `load_best_model_at_end`: False - `ignore_data_skip`: False - `fsdp`: [] - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False} - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None} - `parallelism_config`: None - `deepspeed`: None - `label_smoothing_factor`: 0.0 - `optim`: adamw_torch_fused - `optim_args`: None - `group_by_length`: False - `length_column_name`: length - `project`: huggingface - `trackio_space_id`: trackio - `ddp_find_unused_parameters`: None - `ddp_bucket_cap_mb`: None - `ddp_broadcast_buffers`: False - `dataloader_pin_memory`: True - `dataloader_persistent_workers`: False - `skip_memory_metrics`: True - `push_to_hub`: False - `resume_from_checkpoint`: None - `hub_model_id`: None - `hub_strategy`: every_save - `hub_private_repo`: None - `hub_always_push`: False - `hub_revision`: None - `gradient_checkpointing`: False - `gradient_checkpointing_kwargs`: None - `include_for_metrics`: [] - `eval_do_concat_batches`: True - `auto_find_batch_size`: False - `full_determinism`: False - `ddp_timeout`: 1800 - `torch_compile`: False - `torch_compile_backend`: None - `torch_compile_mode`: None - `include_num_input_tokens_seen`: no - `neftune_noise_alpha`: None - `optim_target_modules`: None - `batch_eval_metrics`: False - `eval_on_start`: False - `use_liger_kernel`: False - `liger_kernel_config`: None - `eval_use_gather_object`: False - `average_tokens_across_devices`: True - `use_cache`: False - `prompts`: None - `batch_sampler`: batch_sampler - `multi_dataset_batch_sampler`: round_robin - `router_mapping`: {} - `learning_rate_mapping`: {}
### Training Logs | Epoch | Step | Training Loss | |:------:|:----:|:-------------:| | 0.2279 | 500 | 0.5229 | | 0.4558 | 1000 | 0.4447 | | 0.6837 | 1500 | 0.4322 | | 0.9116 | 2000 | 0.4234 | ### Framework Versions - Python: 3.10.12 - Sentence Transformers: 5.2.2 - Transformers: 5.1.0 - PyTorch: 2.10.0+cu128 - Accelerate: 1.12.0 - Datasets: 4.5.0 - Tokenizers: 0.22.2 ## Citation ### BibTeX #### Sentence Transformers and SoftmaxLoss ```bibtex @inproceedings{reimers-2019-sentence-bert, title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", author = "Reimers, Nils and Gurevych, Iryna", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", month = "11", year = "2019", publisher = "Association for Computational Linguistics", url = "https://arxiv.org/abs/1908.10084", } ```