Text Classification
Transformers
Safetensors
distilbert
pytorch_model_hub_mixin
model_hub_mixin
custom_code
text-embeddings-inference
Instructions to use cshin23/multidim-rm_reg_gating_prototype with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cshin23/multidim-rm_reg_gating_prototype with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cshin23/multidim-rm_reg_gating_prototype", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cshin23/multidim-rm_reg_gating_prototype", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("cshin23/multidim-rm_reg_gating_prototype", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Push model using huggingface_hub.
Browse files- README.md +9 -0
- model.safetensors +3 -0
README.md
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---
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tags:
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- pytorch_model_hub_mixin
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- model_hub_mixin
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---
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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- Library: [More Information Needed]
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- Docs: [More Information Needed]
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ff2215d6de83970c7a1899aa586585eb2db9434ccd30fd4b96e0f992e28ed2f2
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size 275195776
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