Merge branch 'main' into integration/sentence_transformers
Browse files- README.md +1 -0
- config.json +3 -3
README.md
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@@ -2685,6 +2685,7 @@ sentences = ['What is TSNE?', 'Who is Laurens van der Maaten?']
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tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
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model = AutoModel.from_pretrained('nomic-ai/nomic-embed-text-v1', trust_remote_code=True)
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encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
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tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
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model = AutoModel.from_pretrained('nomic-ai/nomic-embed-text-v1', trust_remote_code=True)
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model.eval()
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encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
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config.json
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@@ -12,7 +12,7 @@
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"bos_token_id": null,
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"causal": false,
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"dense_seq_output": true,
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-
"embd_pdrop": 0.
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"eos_token_id": null,
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"fused_bias_fc": true,
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"fused_dropout_add_ln": true,
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@@ -32,7 +32,7 @@
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"prenorm": false,
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"qkv_proj_bias": false,
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"reorder_and_upcast_attn": false,
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-
"resid_pdrop": 0.
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"rotary_emb_base": 1000,
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"rotary_emb_fraction": 1.0,
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"rotary_emb_interleaved": false,
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@@ -41,7 +41,7 @@
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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-
"summary_first_dropout": 0.
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"bos_token_id": null,
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"causal": false,
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"dense_seq_output": true,
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+
"embd_pdrop": 0.0,
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"eos_token_id": null,
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"fused_bias_fc": true,
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"fused_dropout_add_ln": true,
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"prenorm": false,
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"qkv_proj_bias": false,
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"reorder_and_upcast_attn": false,
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+
"resid_pdrop": 0.0,
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"rotary_emb_base": 1000,
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"rotary_emb_fraction": 1.0,
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"rotary_emb_interleaved": false,
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| 41 |
"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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+
"summary_first_dropout": 0.0,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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