Text Retrieval
Safetensors
sentence-transformers
PyLate
xlm-roberta
ColBERT
feature-extraction
Generated from Trainer
dataset_size:118938
loss:Contrastive
Eval Results (legacy)
Instructions to use rasyosef/colbert-amharic-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rasyosef/colbert-amharic-medium with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="rasyosef/colbert-amharic-medium") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
File size: 1,622 Bytes
8194258 | 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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | {
"added_tokens_decoder": {
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"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<pad>",
"lstrip": false,
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"single_word": false,
"special": true
},
"2": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"3": {
"content": "<unk>",
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"single_word": false,
"special": true
},
"4": {
"content": "<mask>",
"lstrip": true,
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"rstrip": false,
"single_word": false,
"special": true
},
"32000": {
"content": "[Q] ",
"lstrip": false,
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},
"32001": {
"content": "[D] ",
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"normalized": true,
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"special": false
}
},
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"cls_token": "<s>",
"eos_token": "</s>",
"extra_special_tokens": {},
"mask_token": "<mask>",
"max_length": 510,
"model_max_length": 510,
"pad_token": "<mask>",
"sep_token": "</s>",
"stride": 0,
"tokenizer_class": "XLMRobertaTokenizer",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "<unk>"
}
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