Instructions to use ENLP/mrasp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENLP/mrasp2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="ENLP/mrasp2", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ENLP/mrasp2", trust_remote_code=True) model = AutoModel.from_pretrained("ENLP/mrasp2", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac401db2c223e87fa18985315c7e4371fa6e3adeb332f21c89ab0e881a0f0ec3
- Size of remote file:
- 1.51 GB
- SHA256:
- cb2b92d7745ed24143b67c85e596f5ca555ae2f33ff2e0ffb650052257793c14
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