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License
apache-2.0
Tasks
token-classification
Frameworks
gliner
Hardware-aware snippets
Runtime-specific quick starts for urchade/gliner_medium-v2.1. Detected hardware: No explicit hardware metadata.
Task: token-classificationTransformers
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 = "urchade/gliner_medium-v2.1"
pipe = pipeline(
task="token-classification",
model=model_id,
device_map="auto",
model_kwargs={"torch_dtype": "auto"},
)
print(pipe("Hello from Inferix"))
PYModel lineage
1 reposBase model
urchade/gliner_medium-v2.1
Finetuned
1gliner_medium-v2.1selected
Quantizations
0No quantization variants detected.
Model info
Namespace
urchade
Visibility
public
Downloads
2
Likes
0
License: apache-2.0
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Metadata links
Base model
Not specifiedTrained on datasets
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0/0 fitNot available for inference yet.
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Tags
importedhuggingfaceminioglinerpytorchsafetensorstoken-classificationendataset:urchade/pile-mistral-v0.1arxiv:2311.08526license:apache-2.0region:us