# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("zgh36/HRoom")
model = AutoModelForMaskedLM.from_pretrained("zgh36/HRoom")Quick Links
HRoom
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 4.41.0
- TensorFlow 2.15.0
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 4
Model tree for zgh36/HRoom
Base model
almanach/camembert-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zgh36/HRoom")