# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("wfisher27/learning")
model = AutoModelForMaskedLM.from_pretrained("wfisher27/learning")Quick Links
learning
This model is a fine-tuned version of camembert-base on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.36.0.dev0
- TensorFlow 2.15.0
- Datasets 2.15.0
- Tokenizers 0.15.0
- Downloads last month
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Model tree for wfisher27/learning
Base model
almanach/camembert-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="wfisher27/learning")