Instructions to use Lolalb/local_hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lolalb/local_hf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Lolalb/local_hf")# Load model directly from transformers import AutoModelWithLMHead model = AutoModelWithLMHead.from_pretrained("Lolalb/local_hf", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 698 Bytes
e59f763 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"architectures": [
"NeoBERTLMHead"
],
"classifier_init_range": 0.02,
"decoder_init_range": 0.02,
"dim_head": 64,
"embedding_init_range": 0.02,
"hidden_size": 768,
"intermediate_size": 3072,
"kwargs": {
"classifier_init_range": 0.02,
"pretrained_model_name_or_path": "google-bert/bert-base-uncased",
"trust_remote_code": true
},
"max_length": 4096,
"model_type": "neobert",
"norm_eps": 1e-05,
"num_attention_heads": 12,
"num_hidden_layers": 28,
"pad_token_id": 0,
"pretrained_model_name_or_path": "google-bert/bert-base-uncased",
"torch_dtype": "float32",
"transformers_version": "4.48.3",
"trust_remote_code": true,
"vocab_size": 30522
}
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