6x smaller than Naver's official splade-v3-distilbert while having 85% of it's performance on the MSMARCO benchmark. This model is small enough to be used without a GPU on a dataset of a few thousand documents.Collection: https://huggingface.co/collections/rasyosef/splade-tiny-msmarco-687c548c0691d95babf65b70Distillation Dataset: https://huggingface.co/datasets/yosefw/msmarco-train-distil-v2Code: https://github.com/rasyosef/splade-tiny-msmarco| Size (# Params) | MRR@10 (MS MARCO dev) | |
|---|---|---|
BM25 | - | 18.0 |
rasyosef/splade-tiny | 4.4M | 30.9 |
rasyosef/splade-mini | 11.2M | 34.1 |
rasyosef/splade-small | 28.8M | 35.4 |
naver/splade-v3-distilbert | 67.0M | 38.7 |
pip install -U sentence-transformers1from sentence_transformers import SparseEncoder
2
3# Download from the 🤗 Hub
4model = SparseEncoder("rasyosef/splade-mini")
5# Run inference
6queries = [
7 "common law implied warranty",
8]
9documents = [
10 'The law recognizes two basic kinds of warrantiesimplied warranties and express warranties. Implied Warranties. Implied warranties are unspoken, unwritten promises, created by state law, that go from you, as a seller or merchant, to your customers.',
11 'An implied warranty is a contract law term for certain assurances that are presumed in the sale of products or real property.',
12 'The implied warranty of fitness for a particular purpose is a promise that the law says you, as a seller, make when your customer relies on your advice that a product can be used for some specific purpose.',
13]
14query_embeddings = model.encode_query(queries)
15document_embeddings = model.encode_document(documents)
16print(query_embeddings.shape, document_embeddings.shape)
17# [1, 30522] [3, 30522]
18
19# Get the similarity scores for the embeddings
20similarities = model.similarity(query_embeddings, document_embeddings)
21print(similarities)
22# tensor([[22.4364, 22.7160, 21.7330]])SparseEncoder(
(0): MLMTransformer({'max_seq_length': 512, 'do_lower_case': False, 'architecture': 'BertForMaskedLM'})
(1): SpladePooling({'pooling_strategy': 'max', 'activation_function': 'relu', 'word_embedding_dimension': 30522})
)SparseInformationRetrievalEvaluator| Metric | Value |
|---|---|
| dot_accuracy@1 | 0.5018 |
| dot_accuracy@3 | 0.8286 |
| dot_accuracy@5 | 0.9194 |
| dot_accuracy@10 | 0.9746 |
| dot_precision@1 | 0.5018 |
| dot_precision@3 | 0.2839 |
| dot_precision@5 | 0.191 |
| dot_precision@10 | 0.1026 |
| dot_recall@1 | 0.4868 |
| dot_recall@3 | 0.8148 |
| dot_recall@5 | 0.9096 |
| dot_recall@10 | 0.9709 |
| dot_ndcg@10 | 0.7457 |
| dot_mrr@10 | 0.6749 |
| dot_map@100 | 0.6708 |
| query_active_dims | 22.585 |
| query_sparsity_ratio | 0.9993 |
| corpus_active_dims | 174.852 |
| corpus_sparsity_ratio | 0.9943 |
query, positive, negative_1, negative_2, and label| query | positive | negative_1 | negative_2 | label | |
|---|---|---|---|---|---|
| type | string | string | string | string | list |
| details |
|
|
|
|
|
| query | positive | negative_1 | negative_2 | label |
|---|---|---|---|---|
friendly home health care | Medicare Evaluation of the Quality of Care. The quality of care given at Friendly Care Home Health Services is periodically evaluated by Medicare. The results of the most recent evaluation period are listed below to help you compare home care agencies in your area. More Info. | Every participant took the same survey so it is a useful way to compare Friendly Care Home Health Services to other home care agencies. | It covers a wide range of services and can often delay the need for long-term nursing home care. More specifically, home health care may include occupational and physical therapy, speech therapy, and even skilled nursing. | [1.2647171020507812, 9.144136428833008] |
how much does the xbox elite controller weigh | How much does an Xbox 360 weigh? A: The weight of an Xbox 360 depends on the different model purchased, with an original Xbox 360 or Xbox 360 Elite weighing 7.7 pounds with a hard drive and a newer Xbox 360 Slim weighing 6.3 pounds. An Xbox 360 without a hard drive weighs 7 pounds. | How much does 6 xbox 360 games/cases weigh? How much does an xbox 360 elite weigh (in the box)? How much does an xbox 360 weigh? im going to fedex one? I am considering purchasing an Xbox 360, or a Playstation 3... | 1 You can only upload videos smaller than 600 MB. 2 You can only upload a photo (png, jpg, jpeg) or video (3gp, 3gpp, mp4, mov, avi, mpg, mpeg, rm). 3 You can only upload a photo or video. Video should be smaller than [object Object]. | [4.903870582580566, 18.162578582763672] |
what county is norfolk, ct in | Norfolk, Connecticut. Norfolk (local /ˈnɔːrfɔːrk/) is a town in Litchfield County, Connecticut, United States. The population was 1,787 at the 2010 census. | Norfolk Historic District. The Norfolk Historic District was listed on the National Register of Historic Places in 1979. Portions of the content on this web page were adapted from a copy of the original nomination document. [†] Adaptation copyright © 2010, The Gombach Group. Description. | Terms begin the first day of the month. Grand Juries, 1st and 3rd Wednesday of each month. Civil cases set by agreement of counsel and consent of the court; scheduling orders are mandatory in most cases. Civil and Criminal trials begin at 9:30 a.m. | [12.4237699508667, 21.46290397644043] |
SpladeLoss with these parameters:
1{
2 "loss": "SparseMarginMSELoss",
3 "document_regularizer_weight": 0.12,
4 "query_regularizer_weight": 0.2
5}eval_strategy: epochper_device_train_batch_size: 64per_device_eval_batch_size: 64learning_rate: 4e-05num_train_epochs: 4lr_scheduler_type: cosinewarmup_ratio: 0.025fp16: Trueload_best_model_at_end: Trueoptim: adamw_torch_fusedoverwrite_output_dir: Falsedo_predict: Falseeval_strategy: epochprediction_loss_only: Trueper_device_train_batch_size: 64per_device_eval_batch_size: 64per_gpu_train_batch_size: Noneper_gpu_eval_batch_size: Nonegradient_accumulation_steps: 1eval_accumulation_steps: Nonetorch_empty_cache_steps: Nonelearning_rate: 4e-05weight_decay: 0.0adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08max_grad_norm: 1.0num_train_epochs: 4max_steps: -1lr_scheduler_type: cosinelr_scheduler_kwargs: {}warmup_ratio: 0.025warmup_steps: 0log_level: passivelog_level_replica: warninglog_on_each_node: Truelogging_nan_inf_filter: Truesave_safetensors: Truesave_on_each_node: Falsesave_only_model: Falserestore_callback_states_from_checkpoint: Falseno_cuda: Falseuse_cpu: Falseuse_mps_device: Falseseed: 42data_seed: Nonejit_mode_eval: Falseuse_ipex: Falsebf16: Falsefp16: Truefp16_opt_level: O1half_precision_backend: autobf16_full_eval: Falsefp16_full_eval: Falsetf32: Nonelocal_rank: 0ddp_backend: Nonetpu_num_cores: Nonetpu_metrics_debug: Falsedebug: []dataloader_drop_last: Falsedataloader_num_workers: 0dataloader_prefetch_factor: Nonepast_index: -1disable_tqdm: Falseremove_unused_columns: Truelabel_names: Noneload_best_model_at_end: Trueignore_data_skip: Falsefsdp: []fsdp_min_num_params: 0fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap: Noneaccelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed: Nonelabel_smoothing_factor: 0.0optim: adamw_torch_fusedoptim_args: Noneadafactor: Falsegroup_by_length: Falselength_column_name: lengthddp_find_unused_parameters: Noneddp_bucket_cap_mb: Noneddp_broadcast_buffers: Falsedataloader_pin_memory: Truedataloader_persistent_workers: Falseskip_memory_metrics: Trueuse_legacy_prediction_loop: Falsepush_to_hub: Falseresume_from_checkpoint: Nonehub_model_id: Nonehub_strategy: every_savehub_private_repo: Nonehub_always_push: Falsehub_revision: Nonegradient_checkpointing: Falsegradient_checkpointing_kwargs: Noneinclude_inputs_for_metrics: Falseinclude_for_metrics: []eval_do_concat_batches: Truefp16_backend: autopush_to_hub_model_id: Nonepush_to_hub_organization: Nonemp_parameters:auto_find_batch_size: Falsefull_determinism: Falsetorchdynamo: Noneray_scope: lastddp_timeout: 1800torch_compile: Falsetorch_compile_backend: Nonetorch_compile_mode: Noneinclude_tokens_per_second: Falseinclude_num_input_tokens_seen: Falseneftune_noise_alpha: Noneoptim_target_modules: Nonebatch_eval_metrics: Falseeval_on_start: Falseuse_liger_kernel: Falseliger_kernel_config: Noneeval_use_gather_object: Falseaverage_tokens_across_devices: Falseprompts: Nonebatch_sampler: batch_samplermulti_dataset_batch_sampler: proportionalrouter_mapping: {}learning_rate_mapping: {}| Epoch | Step | Training Loss | dot_ndcg@10 |
|---|---|---|---|
| 1.0 | 15625 | 9.3147 | 0.7353 |
| 2.0 | 31250 | 7.5267 | 0.7429 |
| 3.0 | 46875 | 6.3289 | 0.7457 |
1@misc{alemneh2025splademini,
2 author = {Yosef Worku Alemneh},
3 title = {SPLADE-Mini},
4 year = {2025},
5 url = {https://huggingface.co/rasyosef/splade-mini},
6 note = {Hugging Face model repository}
7}