Model: Devy1/MiniLM-cosqa-128
Author: Devy1
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, bert, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:9020, loss:MultipleNegativesRankingLoss, arxiv:1908.10084, arxiv:1705.00652, base_model:sentence-transformers/all-MiniLM-L6-v2, base_model:finetune:sentence-transformers/all-MiniLM-L6-v2, text-embeddings-inference, endpoints_compatible, region:us
Base models (finetune): id: sentence-transformers/all-MiniLM-L6-v2
Card metadata: tags: sentence-transformers, sentence-similarity, feature-extraction, dense, generated_from_trainer, dataset_size:9020, loss:MultipleNegativesRankingLoss
base_model: sentence-transformers/all-MiniLM-L6-v2
widget: source_sentence: python multiprocessing show cpu count
sentences: def unique(seq):
    """Return the unique elements of a collection even if those elements are
       unhashable and unsortable, like dicts and sets"""
    cleaned = []
    for each in seq:
        if each not in cleaned:
            cleaned.append(each)
    return cleaned, def is_in(self, point_x, point_y):
        """ Test if a point is within this polygonal region """

        point_array = array(((point_x, point_y),))
        vertices = array(self.points)
        winding = self.inside_rule == "winding"
        result = points_in_polygon(point_array, vertices, winding)
        return result[0], def machine_info():
    """Retrieve core and memory information for the current machine.
    """
    import psutil
    BYTES_IN_GIG = 1073741824.0
    free_bytes = psutil.virtual_memory().total
    return [{"memory": float("%.1f" % (free_bytes / BYTES_IN_GIG)), "cores": multiprocessing.cpu_count(),
             "name": socket.gethostname()}], source_sentence: python subplot set the whole title
sentences: def set_title(self, title, **kwargs):
        """Sets the title on the underlying matplotlib AxesSubplot."""
        ax = self.get_axes()
        ax.set_title(title, **kwargs), def moving_average(array, n=3):
    """
    Calculates the moving average of an array.

    Parameters
    ----------
    array : array
        The array to have the moving average taken of
    n : int
        The number of points of moving average to take
    
    Returns
    -------
    MovingAverageArray : array
        The n-point moving average of the input array
    """
    ret = _np.cumsum(array, dtype=float)
    ret[n:] = ret[n:] - ret[:-n]
    return ret[n - 1:] / n, def to_query_parameters(parameters):
    """Converts DB-API parameter values into query parameters.

    :type parameters: Mapping[str, Any] or Sequence[Any]
    :param parameters: A dictionary or sequence of query parameter values.

    :rtype: List[google.cloud.bigquery.query._AbstractQueryParameter]
    :returns: A list of query parameters.
    """
    if parameters is None:
        return []

    if isinstance(parameters, collections_abc.Mapping):
        return to_query_parameters_dict(parameters)

    return to_query_parameters_list(parameters), source_sentence: python merge two set to dict
sentences: def make_regex(separator):
    """Utility function to create regexp for matching escaped separators
    in strings.

    """
    return re.compile(r'(?:' + re.escape(separator) + r')?((?:[^' +
                      re.escape(separator) + r'\\]|\\.)+)'), def csvtolist(inputstr):
    """ converts a csv string into a list """
    reader = csv.reader([inputstr], skipinitialspace=True)
    output = []
    for r in reader:
        output += r
    return output, def dict_merge(set1, set2):
    """Joins two dictionaries."""
    return dict(list(set1.items()) + list(set2.items())), source_sentence: python string % substitution float
sentences: def _configure_logger():
    """Configure the logging module."""
    if not app.debug:
        _configure_logger_for_production(logging.getLogger())
    elif not app.testing:
        _configure_logger_for_debugging(logging.getLogger()), def __set__(self, instance, value):
        """ Set a related object for an instance. """

        self.map[id(instance)] = (weakref.ref(instance), value), def format_float(value): # not used
    """Modified form of the 'g' format specifier.
    """
    string = "{:g}".format(value).replace("e+", "e")
    string = re.sub("e(-?)0*(\d+)", r"e\1\2", string)
    return string, source_sentence: bottom 5 rows in python
sentences: def refresh(self, document):
		""" Load a new copy of a document from the database.  does not
			replace the old one """
		try:
			old_cache_size = self.cache_size
			self.cache_size = 0
			obj = self.query(type(document)).filter_by(mongo_id=document.mongo_id).one()
		finally:
			self.cache_size = old_cache_size
		self.cache_write(obj)
		return obj, def table_top_abs(self):
        """Returns the absolute position of table top"""
        table_height = np.array([0, 0, self.table_full_size[2]])
        return string_to_array(self.floor.get("pos")) + table_height, def get_dimension_array(array):
    """
    Get dimension of an array getting the number of rows and the max num of
    columns.
    """
    if all(isinstance(el, list) for el in array):
        result = [len(array), len(max([x for x in array], key=len,))]

    # elif array and isinstance(array, list):
    else:
        result = [len(array), 1]

    return result
pipeline_tag: sentence-similarity
library_name: sentence-transformers
Likes: 0 | All-time downloads: 34
Created: 2025-09-30 20:49:25