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License
mit
Tasks
fill-mask
Frameworks
transformers
Hardware-aware snippets
Runtime-specific quick starts for GottBERT/GottBERT_base_last. Detected hardware: No explicit hardware metadata.
Task: fill-maskTransformers
NVIDIA CUDA path
Best default for NVIDIA GPUs and hosted accelerator nodes.
pip install torch transformers accelerate
python - <<'PY'
from transformers import pipeline
model_id = "GottBERT/GottBERT_base_last"
pipe = pipeline(
task="fill-mask",
model=model_id,
device_map="auto",
model_kwargs={"torch_dtype": "auto"},
)
print(pipe("Hello from Inferix"))
PYModel lineage
1 reposBase model
GottBERT/GottBERT_base_last
Finetuned
1GottBERT_base_lastselected
Quantizations
0No quantization variants detected.
Model info
Namespace
GottBERT
Visibility
public
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0
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0
License: mit
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No evaluation results published yet.
Metadata links
Base model
Not specifiedTrained on datasets
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Inference providers
0/0 fitNot available for inference yet.
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Tags
importedhuggingfaceminiotransformerspytorchjaxsafetensorsrobertafill-maskRoBERTaGottBERTBERTdearxiv:2012.02110license:mitendpoints_compatibledeploy:azureregion:us