Instructions to use hcoxec/BERT_4L_128H_A2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hcoxec/BERT_4L_128H_A2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hcoxec/BERT_4L_128H_A2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hcoxec/BERT_4L_128H_A2") model = AutoModel.from_pretrained("hcoxec/BERT_4L_128H_A2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hcoxec/BERT_4L_128H_A2: direct link, hf CLI and curl.
- Browser
- Download file 19.1 MB
-
https://huggingface.co/hcoxec/BERT_4L_128H_A2/resolve/main/model.safetensors
- Command line
-
hf download hf://hcoxec/BERT_4L_128H_A2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hcoxec/BERT_4L_128H_A2/resolve/main/model.safetensors
19.1 MB
- Xet hash:
- 28a0ab3b8f3b2a6cd32a0ef66522061fb7321ccb3aefcaf1b797a3700a7212f5
- Size of remote file:
- 19.1 MB
- SHA256:
- f21512b95487b82255132959bfe932d91377a4b52880f8c3c2b69c29114515a1
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