Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 160, in _generate_tables
df = pandas_read_json(f)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1025, in read
obj = self._get_object_parser(self.data)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1051, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1187, in parse
self._parse()
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/json/_json.py", line 1403, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 231, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2998, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1918, in _head
return _examples_to_batch(list(self.take(n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2093, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1576, in __iter__
for key_example in islice(self.ex_iterable, self.n - ex_iterable_num_taken):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 279, in __iter__
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 163, in _generate_tables
raise e
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 137, in _generate_tables
pa_table = paj.read_json(
File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
Hindi to English Translation Model
This repository contains a pre-trained machine translation model for translating text from Hindi to English. The model is based on the Helsinki-NLP/opus-mt-hi-en model, utilizing the Transformers framework.
Model Details
- Model Name: Helsinki-NLP/opus-mt-hi-en
- Language: Hindi to English
- Framework: Transformers (Hugging Face)
- License: Apache 2.0
Installation
To use this model, install the required dependencies:
pip install transformers torch
Usage
You can use this model with the Hugging Face transformers library as follows:
from transformers import MarianMTModel, MarianTokenizer
def translate(text):
model_name = "Helsinki-NLP/opus-mt-hi-en"
tokenizer = MarianTokenizer.from_pretrained(model_name)
model = MarianMTModel.from_pretrained(model_name)
# Tokenize input text
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
# Generate translation
translated_tokens = model.generate(**inputs)
translation = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True)
return translation[0]
# Example usage
hindi_text = "\u092e\u0947\u0930\u093e \u0928\u093e\u092e \u0930\u093e\u0939\u0941\u0932 \u0939\u0948"
english_translation = translate(hindi_text)
print("Translation:", english_translation)
License
This project is licensed under the Apache 2.0 License. See the LICENSE file for more details.
Acknowledgments
- Helsinki-NLP for providing the OPUS-MT model.
- Hugging Face for the
transformerslibrary.
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