Instructions to use cmarkea/distilcamembert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cmarkea/distilcamembert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cmarkea/distilcamembert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cmarkea/distilcamembert-base") model = AutoModelForMaskedLM.from_pretrained("cmarkea/distilcamembert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Cyrile Delestre commited on
Commit ·
df1a58e
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Parent(s): f0bcb7f
Update config.json
Browse files- config.json +1 -1
config.json
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"output_hidden_states": false,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "camembert",
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"output_hidden_states": false,
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