Instructions to use seanghay/albert-khmer-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seanghay/albert-khmer-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="seanghay/albert-khmer-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("seanghay/albert-khmer-small") model = AutoModelForMaskedLM.from_pretrained("seanghay/albert-khmer-small") - Notebooks
- Google Colab
- Kaggle
Upload AlbertForMaskedLM
Browse files- config.json +1 -1
- model.safetensors +2 -2
config.json
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"position_embedding_type": "absolute",
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"transformers_version": "4.57.3",
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"type_vocab_size": 2,
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"vocab_size":
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}
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"position_embedding_type": "absolute",
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"transformers_version": "4.57.3",
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"type_vocab_size": 2,
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"vocab_size": 16000
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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size 37666248
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