Instructions to use ENLP/mrasp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ENLP/mrasp 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/mrasp", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ENLP/mrasp", trust_remote_code=True) model = AutoModel.from_pretrained("ENLP/mrasp", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b1bdab54485762fe4a53c67d0352877f27be3b00c3ab11e0b784e05a7a9ac6d
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size 973645080
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