Instructions to use Arvind0101/static-query-splade-code-docs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arvind0101/static-query-splade-code-docs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Arvind0101/static-query-splade-code-docs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Arvind0101/static-query-splade-code-docs") model = AutoModelForMaskedLM.from_pretrained("Arvind0101/static-query-splade-code-docs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Arvind0101/static-query-splade-code-docs: direct link, hf CLI and curl.
- Browser
- Download file 1.2 kB
-
https://huggingface.co/Arvind0101/static-query-splade-code-docs/resolve/main/config.json
- Command line
-
hf download hf://Arvind0101/static-query-splade-code-docs/config.json
-
curl -L -o config.json https://huggingface.co/Arvind0101/static-query-splade-code-docs/resolve/main/config.json
1.2 kB
| { | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "BertForMaskedLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": null, | |
| "classifier_dropout": null, | |
| "document_chunk_length": 512, | |
| "document_pooling": "max_log1p_relu", | |
| "dtype": "float32", | |
| "eos_token_id": null, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "inference_free_query": true, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "is_decoder": false, | |
| "layer_norm_eps": 1e-12, | |
| "max_chunks_per_document": 2, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 3, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "pruned_from_checkpoint": "/vol/static_splade/numpy_pandas_pybind11_v1/checkpoints/splade_v3_doc_static_full_v3_stronger_flops/best_proxy", | |
| "pruned_layer_indices": [ | |
| 0, | |
| 6, | |
| 11 | |
| ], | |
| "query_encoder_type": "learned_static_token_weights", | |
| "static_query_weight_file": "static_query_weights.pt", | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.13.1", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |