Sentence Similarity
sentence-transformers
Safetensors
Haitian
gemma3_text
trimmed
text-embeddings-inference
Instructions to use alphaedge-ai/embeddinggemma-hat-16384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use alphaedge-ai/embeddinggemma-hat-16384 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("alphaedge-ai/embeddinggemma-hat-16384") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Trimmed EmbeddingGemma 300M for Haitian
Browse files- 1_Pooling/config.json +10 -0
- 2_Dense/config.json +6 -0
- 2_Dense/model.safetensors +3 -0
- 3_Dense/config.json +6 -0
- 3_Dense/model.safetensors +3 -0
- README.md +49 -0
- config.json +61 -0
- config_sentence_transformers.json +26 -0
- generation_config.json +7 -0
- model.safetensors +3 -0
- modules.json +32 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +85 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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2_Dense/config.json
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{
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"in_features": 768,
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"out_features": 3072,
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"bias": false,
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"activation_function": "torch.nn.modules.linear.Identity"
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}
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2_Dense/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c327f2acb00149676ade24a75e11eb6ebbd367f9ee050267ba56829d2979f702
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size 9437272
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3_Dense/config.json
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{
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"in_features": 3072,
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"out_features": 768,
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"bias": false,
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"activation_function": "torch.nn.modules.linear.Identity"
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}
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3_Dense/model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ffb6cc5162e11e2ce6bc2367e121ee3bbbc4e82e1ee26826bd7573d4948d81b8
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size 9437272
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README.md
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---
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pipeline_tag: fill-mask
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language: hat
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tags:
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- trimmed
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library_name: transformers
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base_model: google/embeddinggemma-300m
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base_model_relation: quantized
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datasets:
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- Lumberjackk/fineweb-2-trimming
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---
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# embeddinggemma-hat-16384
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This model is a 62.3% smaller version of [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m)
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optimized for Haitian language via vocabulary trimming mined on [Lumberjackk/fineweb-2-trimming](https://huggingface.co/datasets/Lumberjackk/fineweb-2-trimming).
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## Model Statistics
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- **Original vocabulary size:** 262,144 tokens
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- **Trimmed vocabulary size:** 16,384 tokens
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- **Vocabulary reduction:** 93.7%
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- **Original model size:** 302,863,104 parameters
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- **Trimmed model size:** 114,119,424 parameters
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- **Size reduction:** 62.3%
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## Usage
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```python
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from sentence_transformers import SentenceTransformer
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# Download from the 🤗 Hub
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model = SentenceTransformer("embeddinggemma-hat-16384")
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# Run inference with queries and documents
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query = "My query"
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documents = [
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"Chunk 1",
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"Chunk 2",
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"Chunk 3",
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]
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query_embeddings = model.encode_query(query)
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document_embeddings = model.encode_document(documents)
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print(query_embeddings.shape, document_embeddings.shape)
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# Compute similarities to determine a ranking
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similarities = model.similarity(query_embeddings, document_embeddings)
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print(similarities)
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```
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config.json
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{
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"_sliding_window_pattern": 6,
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"architectures": [
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"Gemma3TextModel"
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],
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| 6 |
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"attention_bias": false,
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| 7 |
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"attention_dropout": 0.0,
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| 8 |
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"attn_logit_softcapping": null,
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| 9 |
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"bos_token_id": 2,
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| 10 |
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"dtype": "float32",
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| 11 |
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"eos_token_id": 1,
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| 12 |
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"final_logit_softcapping": null,
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| 13 |
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"head_dim": 256,
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| 14 |
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"hidden_activation": "gelu_pytorch_tanh",
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| 15 |
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"hidden_size": 768,
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| 16 |
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"initializer_range": 0.02,
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| 17 |
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"intermediate_size": 1152,
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| 18 |
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"layer_types": [
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"sliding_attention",
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| 20 |
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"sliding_attention",
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| 21 |
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"sliding_attention",
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| 22 |
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"sliding_attention",
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| 23 |
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"sliding_attention",
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| 24 |
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"full_attention",
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| 25 |
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"sliding_attention",
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| 26 |
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"sliding_attention",
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| 27 |
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"sliding_attention",
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| 28 |
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"sliding_attention",
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| 29 |
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"sliding_attention",
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| 30 |
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"full_attention",
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| 31 |
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"sliding_attention",
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| 32 |
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"sliding_attention",
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| 33 |
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"sliding_attention",
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| 34 |
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"sliding_attention",
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| 35 |
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"sliding_attention",
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| 36 |
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"full_attention",
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| 37 |
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"sliding_attention",
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| 38 |
+
"sliding_attention",
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| 39 |
+
"sliding_attention",
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| 40 |
+
"sliding_attention",
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| 41 |
+
"sliding_attention",
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| 42 |
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"full_attention"
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| 43 |
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],
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| 44 |
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"max_position_embeddings": 2048,
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| 45 |
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"model_type": "gemma3_text",
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| 46 |
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"num_attention_heads": 3,
|
| 47 |
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"num_hidden_layers": 24,
|
| 48 |
+
"num_key_value_heads": 1,
|
| 49 |
+
"pad_token_id": 0,
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| 50 |
+
"query_pre_attn_scalar": 256,
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| 51 |
+
"rms_norm_eps": 1e-06,
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| 52 |
+
"rope_local_base_freq": 10000.0,
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| 53 |
+
"rope_scaling": null,
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| 54 |
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"rope_theta": 1000000.0,
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| 55 |
+
"sliding_window": 512,
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| 56 |
+
"torch_dtype": "float32",
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| 57 |
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"transformers_version": "4.55.4",
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| 58 |
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"use_bidirectional_attention": true,
|
| 59 |
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"use_cache": true,
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| 60 |
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"vocab_size": 16384
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| 61 |
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}
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config_sentence_transformers.json
ADDED
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{
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"model_type": "SentenceTransformer",
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"__version__": {
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"sentence_transformers": "5.1.0",
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"transformers": "4.57.0.dev0",
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"pytorch": "2.8.0+cu128"
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| 7 |
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},
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| 8 |
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"prompts": {
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| 9 |
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"query": "task: search result | query: ",
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| 10 |
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"document": "title: none | text: ",
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| 11 |
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"BitextMining": "task: search result | query: ",
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| 12 |
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"Clustering": "task: clustering | query: ",
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| 13 |
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"Classification": "task: classification | query: ",
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| 14 |
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"InstructionRetrieval": "task: code retrieval | query: ",
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| 15 |
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"MultilabelClassification": "task: classification | query: ",
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| 16 |
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"PairClassification": "task: sentence similarity | query: ",
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| 17 |
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"Reranking": "task: search result | query: ",
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| 18 |
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"Retrieval": "task: search result | query: ",
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| 19 |
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"Retrieval-query": "task: search result | query: ",
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| 20 |
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"Retrieval-document": "title: none | text: ",
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| 21 |
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"STS": "task: sentence similarity | query: ",
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| 22 |
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"Summarization": "task: summarization | query: "
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| 23 |
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},
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| 24 |
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"default_prompt_name": null,
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| 25 |
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"similarity_fn_name": "cosine"
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| 26 |
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}
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generation_config.json
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{
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"cache_implementation": "hybrid",
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"do_sample": true,
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| 4 |
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"top_k": 64,
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| 5 |
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"top_p": 0.95,
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"transformers_version": "4.57.0.dev0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:a62ce2543b67ac7cdfcf23ef292a9bc084ea5860c4ad202a94bcf582209c94ae
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size 456510944
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modules.json
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[
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{
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"idx": 0,
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"name": "0",
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| 5 |
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"path": "",
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| 6 |
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"type": "sentence_transformers.models.Transformer"
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| 7 |
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},
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| 8 |
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{
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| 9 |
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"idx": 1,
|
| 10 |
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"name": "1",
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| 11 |
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"path": "1_Pooling",
|
| 12 |
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"type": "sentence_transformers.models.Pooling"
|
| 13 |
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},
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| 14 |
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{
|
| 15 |
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"idx": 2,
|
| 16 |
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"name": "2",
|
| 17 |
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"path": "2_Dense",
|
| 18 |
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"type": "sentence_transformers.models.Dense"
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| 19 |
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},
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| 20 |
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{
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| 21 |
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"idx": 3,
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| 22 |
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"name": "3",
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| 23 |
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"path": "3_Dense",
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| 24 |
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"type": "sentence_transformers.models.Dense"
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| 25 |
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},
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| 26 |
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{
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| 27 |
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"idx": 4,
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| 28 |
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"name": "4",
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| 29 |
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"path": "4_Normalize",
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| 30 |
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"type": "sentence_transformers.models.Normalize"
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| 31 |
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}
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]
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sentence_bert_config.json
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{
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"max_seq_length": 2048,
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| 3 |
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"do_lower_case": false
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}
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special_tokens_map.json
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{
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"bos_token": {
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| 3 |
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"content": "<bos>",
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| 4 |
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"lstrip": false,
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| 5 |
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"normalized": false,
|
| 6 |
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"rstrip": false,
|
| 7 |
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"single_word": false
|
| 8 |
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},
|
| 9 |
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"eos_token": {
|
| 10 |
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"content": "<eos>",
|
| 11 |
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"lstrip": false,
|
| 12 |
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"normalized": false,
|
| 13 |
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"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "<pad>",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
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"single_word": false
|
| 22 |
+
},
|
| 23 |
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"unk_token": {
|
| 24 |
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"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
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"single_word": false
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| 29 |
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}
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| 30 |
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}
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tokenizer.json
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tokenizer_config.json
ADDED
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@@ -0,0 +1,85 @@
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|
| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"0": {
|
| 4 |
+
"content": "<pad>",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"1": {
|
| 12 |
+
"content": "<eos>",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"2": {
|
| 20 |
+
"content": "<bos>",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"3": {
|
| 28 |
+
"content": "<unk>",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": false,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
},
|
| 35 |
+
"4": {
|
| 36 |
+
"content": "\n",
|
| 37 |
+
"lstrip": false,
|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": false
|
| 42 |
+
},
|
| 43 |
+
"5": {
|
| 44 |
+
"content": "\n\n",
|
| 45 |
+
"lstrip": false,
|
| 46 |
+
"normalized": false,
|
| 47 |
+
"rstrip": false,
|
| 48 |
+
"single_word": false,
|
| 49 |
+
"special": false
|
| 50 |
+
},
|
| 51 |
+
"6": {
|
| 52 |
+
"content": "\n\n\n",
|
| 53 |
+
"lstrip": false,
|
| 54 |
+
"normalized": false,
|
| 55 |
+
"rstrip": false,
|
| 56 |
+
"single_word": false,
|
| 57 |
+
"special": false
|
| 58 |
+
},
|
| 59 |
+
"16382": {
|
| 60 |
+
"content": "<start_of_image>",
|
| 61 |
+
"lstrip": false,
|
| 62 |
+
"normalized": false,
|
| 63 |
+
"rstrip": false,
|
| 64 |
+
"single_word": false,
|
| 65 |
+
"special": true
|
| 66 |
+
},
|
| 67 |
+
"16383": {
|
| 68 |
+
"content": "<end_of_image>",
|
| 69 |
+
"lstrip": false,
|
| 70 |
+
"normalized": false,
|
| 71 |
+
"rstrip": false,
|
| 72 |
+
"single_word": false,
|
| 73 |
+
"special": true
|
| 74 |
+
}
|
| 75 |
+
},
|
| 76 |
+
"bos_token": "<bos>",
|
| 77 |
+
"clean_up_tokenization_spaces": false,
|
| 78 |
+
"eos_token": "<eos>",
|
| 79 |
+
"extra_special_tokens": {},
|
| 80 |
+
"model_max_length": 2048,
|
| 81 |
+
"pad_token": "<pad>",
|
| 82 |
+
"padding_side": "right",
|
| 83 |
+
"tokenizer_class": "PreTrainedTokenizerFast",
|
| 84 |
+
"unk_token": "<unk>"
|
| 85 |
+
}
|