Sentence Similarity
Transformers
Safetensors
multilingual
nllb-llm2vec
feature-extraction
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
text-reranking
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
custom_code
File size: 1,234 Bytes
b0221f6 f19606f 0a0e65e b0221f6 838c37a b0221f6 |
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 |
{
"architectures": [
"NLLBLLM2Vec"
],
"auto_map": {
"AutoConfig": "configuration_nllbllm2vec.NLLBLLM2VecConfig",
"AutoModel": "modeling_nllbllm2vec.NLLBLLM2Vec",
"AutoModelForSequenceClassification": "modeling_nllbllm2vec.NLLBLLM2VecForSequenceClassification",
"AutoModelForTokenClassification": "modeling_nllbllm2vec.NLLBLLM2VecForTokenClassification"
},
"llm2vec_config": {
"_name_or_path": "McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp",
"bos_token_id": 128000,
"eos_token_id": 128001,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"model_type": "llama",
"num_key_value_heads": 8,
"rms_norm_eps": 1e-05,
"rope_theta": 500000,
"torch_dtype": "bfloat16",
"use_cache": false,
"vocab_size": 128256
},
"model_type": "nllb-llm2vec",
"nllb_config": {
"_name_or_path": "facebook/nllb-200-distilled-600M",
"architectures": [
"M2M100Encoder"
],
"decoder_layerdrop": 0,
"encoder_layerdrop": 0,
"max_length": 200,
"model_type": "m2m_100",
"tokenizer_class": "NllbTokenizer",
"torch_dtype": "bfloat16",
"vocab_size": 256206
},
"torch_dtype": "bfloat16",
"transformers_version": "4.45.2"
}
|