Instructions to use monsoon-nlp/ar-seq2seq-gender-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monsoon-nlp/ar-seq2seq-gender-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="monsoon-nlp/ar-seq2seq-gender-encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("monsoon-nlp/ar-seq2seq-gender-encoder") model = AutoModel.from_pretrained("monsoon-nlp/ar-seq2seq-gender-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from monsoon-nlp/ar-seq2seq-gender-encoder: direct link, hf CLI and curl.
- Browser
- Download file 651 MB
-
https://huggingface.co/monsoon-nlp/ar-seq2seq-gender-encoder/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://monsoon-nlp/ar-seq2seq-gender-encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/monsoon-nlp/ar-seq2seq-gender-encoder/resolve/main/pytorch_model.bin
651 MB
- Xet hash:
- de4621fa422168d634a7844730640317889b1c510738977e441df999d6d7bf7e
- Size of remote file:
- 651 MB
- SHA256:
- 9c6871fa024e86bf720b7064542a727dd81a456b8f876c4aa0988b8aa2672f7e
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