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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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## 二、使用方法
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```python
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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model_path = '
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model = AutoModelForSeq2SeqLM.from_pretrained(model_path, trust_remote_code=True, cache_dir=model_path)
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True, cache_dir=model_path)
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input_text = ["Welcome to download and use!"]
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## 二、使用方法
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```python
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from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
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model_path = 'ENLP/mrasp2'
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model = AutoModelForSeq2SeqLM.from_pretrained(model_path, trust_remote_code=True, cache_dir=model_path)
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True, cache_dir=model_path)
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input_text = ["Welcome to download and use!"]
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