Instructions to use FacebookAI/xlm-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FacebookAI/xlm-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FacebookAI/xlm-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("FacebookAI/xlm-roberta-large") model = AutoModelForMaskedLM.from_pretrained("FacebookAI/xlm-roberta-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download src/utils/configuration.py from FacebookAI/xlm-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 3.97 kB
-
https://huggingface.co/FacebookAI/xlm-roberta-large/resolve/refs%2Fpr%2F8/src/utils/configuration.py
- Command line
-
hf download hf://FacebookAI/xlm-roberta-large@refs/pr/8/src/utils/configuration.py
-
curl -L -o configuration.py https://huggingface.co/FacebookAI/xlm-roberta-large/resolve/refs%2Fpr%2F8/src/utils/configuration.py
3.97 kB
| import yaml | |
| import copy | |
| from src.utils.mapper import configmapper | |
| def load_yaml(path): | |
| """ | |
| Function to load a yaml file and | |
| return the collected dict(s) | |
| Parameters | |
| ---------- | |
| path : str | |
| The path to the yaml config file | |
| Returns | |
| ------- | |
| result : dict | |
| The dictionary from the config file | |
| """ | |
| assert isinstance(path, str), "Provided path is not a string" | |
| try: | |
| f = open(path, "r") | |
| result = yaml.load(f, Loader=yaml.Loader) | |
| except FileNotFoundError as e: | |
| # Adding this for future functionality | |
| raise e | |
| return result | |
| def convert_params_to_dict(params): | |
| dic = {} | |
| for k, v in params.as_dict(): | |
| try: | |
| obj = configmapper.get_object("params", v) | |
| dic[k] = v | |
| except: | |
| print( | |
| f"Undefined {v} for the given key: {k} in mapper ,storing original value" | |
| ) | |
| dic[k] = v | |
| return value | |
| class Config: | |
| """Config Class to be used with YAML configuration files | |
| This class can be used to address keys as attributes. | |
| Ensure that there are no spaces between the keys. | |
| Only objects of type dict can be converted to config. | |
| Attributes | |
| ---------- | |
| _config : dict, | |
| The dictionary which is formed from the | |
| yaml file or custom dictionary | |
| Methods | |
| ------- | |
| as_dict(), | |
| Return the config object as dictionary | |
| Possible update: | |
| ## Can be converted using __getattr__ to use **kwargs | |
| ## with the Config object directly. | |
| set_value(attr,value) | |
| Set the value of a particular attribute. | |
| """ | |
| def __init__(self, *, path=None, dic=None): | |
| """ | |
| Initializer for the Config class | |
| Needs either path or the dict object to create the config | |
| Parameters | |
| ---------- | |
| path: str, optional | |
| The path to the config YAML file. | |
| Default value is None. | |
| dic : dict, optional | |
| The dictionary containing the configuration. | |
| Default value is None. | |
| """ | |
| if path: | |
| self._config = load_yaml(path) | |
| elif dict: | |
| self._config = dic | |
| else: | |
| raise Exception("Need either path or dict object to instantiate object.") | |
| # self.keys = self._config.keys() | |
| def __getattr__(self, attr): | |
| """ | |
| Get method for Config class. Helps get keys as attributes. | |
| Parameters | |
| ---------- | |
| attr: The attribute name passed as <object>.attr | |
| Returns | |
| ------- | |
| self._config[attr]: object or Config object | |
| The value of the given key if it exists. | |
| If the value is a dict object, | |
| a Config object of that dict is returned. | |
| Otherwise, the exact value is returned. | |
| Raises | |
| ------ | |
| KeyError() if the given key is not defined. | |
| """ | |
| if attr in self._config: | |
| if isinstance(self._config[attr], dict): | |
| return Config(dic=self._config[attr]) | |
| else: | |
| return self._config[attr] | |
| else: | |
| raise KeyError(f"Key:{attr} not defined.") | |
| def set_value(self, attr, value): | |
| """ | |
| Set method for Config class. Helps set keys in the _config. | |
| Parameters | |
| ---------- | |
| attr: The attribute name passed as <object>.attr | |
| value: The value to be stored as the attr. | |
| """ | |
| self._config[attr] = value | |
| def __str__(self): | |
| """Function to print the dictionary | |
| contained in the object.""" | |
| return self._config.__str__() | |
| def __repr__(self): | |
| return f"Config(dic={self._config})" | |
| def __deepcopy__(self, memo): | |
| return Config(dic=copy.deepcopy(self._config)) | |
| def as_dict(self): | |
| """Function to get the config as dictionary object""" | |
| return dict(self._config) | |