Text Classification
Transformers
ONNX
Safetensors
GLiClass
rlcd
typesafe-ai
jev
decision-engine
system-1
modernbert
gliclass
non-autoregressive
zero-token-generation
structured-outputs
calibration
expected-calibration-error
ece
brier-score
proper-scoring-rules
webgpu
edge-ai
fast-inference
banking77
Instructions to use heman10x/rlcd-modernbert-151m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use heman10x/rlcd-modernbert-151m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="heman10x/rlcd-modernbert-151m")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("heman10x/rlcd-modernbert-151m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_fp16.onnx from heman10x/rlcd-modernbert-151m: direct link, hf CLI and curl.
- Browser
- Download file 304 MB
-
https://huggingface.co/heman10x/rlcd-modernbert-151m/resolve/a0ce803f97922b75c289934b3859b4998e487f86/model_fp16.onnx
- Command line
-
hf download hf://heman10x/rlcd-modernbert-151m@a0ce803f97922b75c289934b3859b4998e487f86/model_fp16.onnx
-
curl -L -o model_fp16.onnx https://huggingface.co/heman10x/rlcd-modernbert-151m/resolve/a0ce803f97922b75c289934b3859b4998e487f86/model_fp16.onnx
304 MB
- Xet hash:
- c17e5fb103959f99fdb9fdf8af0952b8a7cc79b2d80c20ce300ec4394233c150
- Size of remote file:
- 304 MB
- SHA256:
- 6be4931ade91b0e867670d71f8e49de5e0d651493fa37409422e1c42bc4ffd3f
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