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1_Pooling/config.json ADDED
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+ {
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+ "word_embedding_dimension": 1024,
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+ "pooling_mode_cls_token": false,
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README.md CHANGED
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - sentence-transformers
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+ - sentence-similarity
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+ - feature-extraction
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+ pipeline_tag: sentence-similarity
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+ library_name: sentence-transformers
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+ ---
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+
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+ # SentenceTransformer
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+
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+ This is a [sentence-transformers](https://www.SBERT.net) model trained. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.
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+
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+ ## Model Details
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+
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+ ### Model Description
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+ - **Model Type:** Sentence Transformer
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+ <!-- - **Base model:** [Unknown](https://huggingface.co/unknown) -->
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+ - **Maximum Sequence Length:** 128 tokens
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+ - **Output Dimensionality:** 1024 dimensions
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+ - **Similarity Function:** Cosine Similarity
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+ <!-- - **Training Dataset:** Unknown -->
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+ <!-- - **Language:** Unknown -->
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+ <!-- - **License:** Unknown -->
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+
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+ ### Model Sources
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+
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+ - **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
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+ - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
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+ - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
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+
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+ ### Full Model Architecture
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+
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+ ```
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+ SentenceTransformer(
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+ (0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: RobertaModel
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+ (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
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+ (2): Normalize()
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+ )
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+ ```
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+
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+ ## Usage
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+
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+ ### Direct Usage (Sentence Transformers)
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+
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+ First install the Sentence Transformers library:
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+
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+ ```bash
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+ pip install -U sentence-transformers
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+ ```
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+
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+ Then you can load this model and run inference.
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+ ```python
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+ from sentence_transformers import SentenceTransformer
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+
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+ # Download from the 🤗 Hub
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+ model = SentenceTransformer("sentence_transformers_model_id")
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+ # Run inference
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+ sentences = [
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+ 'The weather is lovely today.',
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+ "It's so sunny outside!",
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+ 'He drove to the stadium.',
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+ ]
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+ embeddings = model.encode(sentences)
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+ print(embeddings.shape)
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+ # [3, 1024]
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+
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+ # Get the similarity scores for the embeddings
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+ similarities = model.similarity(embeddings, embeddings)
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+ print(similarities.shape)
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+ # [3, 3]
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+ ```
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+
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+ <!--
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+ ### Direct Usage (Transformers)
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+
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+ <details><summary>Click to see the direct usage in Transformers</summary>
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+
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+ </details>
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+ -->
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+
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+ <!--
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+ ### Downstream Usage (Sentence Transformers)
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+
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+ You can finetune this model on your own dataset.
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+
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+ <details><summary>Click to expand</summary>
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+
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+ </details>
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+ -->
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+
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+ <!--
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+ ### Out-of-Scope Use
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+
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+ *List how the model may foreseeably be misused and address what users ought not to do with the model.*
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+ -->
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+
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+ <!--
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+ ## Bias, Risks and Limitations
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+
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+ *What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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+ -->
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+
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+ <!--
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+ ### Recommendations
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+
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+ *What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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+ -->
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+
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+ ## Training Details
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+
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+ ### Framework Versions
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+ - Python: 3.12.9
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+ - Sentence Transformers: 4.0.1
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+ - Transformers: 4.48.2
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+ - PyTorch: 2.6.0+cu124
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+ - Accelerate: 1.4.0
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+ - Datasets: 3.3.2
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+ - Tokenizers: 0.21.0
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+
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+ ## Citation
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+
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+ ### BibTeX
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+
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+ <!--
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+ ## Glossary
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+
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+ *Clearly define terms in order to be accessible across audiences.*
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+ -->
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+
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+ <!--
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+ ## Model Card Authors
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+
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+ *Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
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+ -->
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+
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+ <!--
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+ ## Model Card Contact
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+
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+ *Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
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+ -->
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+ "[P@@]": 193,
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+ "[Si@H]": 194,
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+ "[Mn+4]": 195,
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+ "p": 196,
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+ "[Ba]": 197,
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+ "[NH2-]": 198,
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+ "[Ge]": 199,
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+ "[Pb+4]": 200,
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+ "[Cr+3]": 201,
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+ "[Au]": 202,
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+ "[LiH]": 203,
304
+ "[Sc+3]": 204,
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+ "[o+]": 205,
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+ "[Rh-3]": 206,
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+ "[Br]": 208,
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+ "[Sb-]": 209,
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+ "[S@+]": 210,
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+ "[I+2]": 211,
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+ "[Ar]": 212,
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+ "[V]": 213,
314
+ "[Cu-]": 214,
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+ "[Al-]": 215,
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+ "[Te]": 216,
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+ "[13c]": 217,
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+ "[13C]": 218,
319
+ "[Cl]": 219,
320
+ "[PH4+]": 220,
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+ "[SiH4]": 221,
322
+ "[te]": 222,
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+ "[CH3-]": 223,
324
+ "[S@@+]": 224,
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+ "[Rh+3]": 225,
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+ "[SH+]": 226,
327
+ "[Bi+3]": 227,
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+ "[Br+2]": 228,
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+ "[La]": 229,
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+ "[La+3]": 230,
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+ "[Pt-2]": 231,
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+ "[N@@]": 232,
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+ "[PH3+]": 233,
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+ "[N@]": 234,
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+ "[Si+4]": 235,
336
+ "[Sr+2]": 236,
337
+ "[Al+]": 237,
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+ "[Pb]": 238,
339
+ "[SeH]": 239,
340
+ "[Si-]": 240,
341
+ "[V+5]": 241,
342
+ "[Y+3]": 242,
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+ "[Re]": 243,
344
+ "[Ru+]": 244,
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+ "[Sm]": 245,
346
+ "*": 246,
347
+ "[3H]": 247,
348
+ "[NH2]": 248,
349
+ "[Ag-]": 249,
350
+ "[13CH3]": 250,
351
+ "[OH+]": 251,
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+ "[Ru+3]": 252,
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+ "[OH]": 253,
354
+ "[Gd+3]": 254,
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+ "[13CH2]": 255,
356
+ "[In+3]": 256,
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+ "[Si@@]": 257,
358
+ "[Si@]": 258,
359
+ "[Ti+2]": 259,
360
+ "[Sn+]": 260,
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+ "[Pd-2]": 263,
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+ "[SnH3]": 264,
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+ "[B+3]": 265,
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+ "[Cu-2]": 266,
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+ "[Nd+3]": 267,
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+ "[Pb+3]": 268,
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+ "[13cH]": 269,
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+ "[Fe-4]": 270,
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+ "[Ga]": 271,
372
+ "[Sn+4]": 272,
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+ "[Hg+]": 273,
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+ "[11CH3]": 274,
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+ "[Hf]": 275,
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+ "[Pr]": 276,
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+ "[Y]": 277,
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+ "[S+2]": 278,
379
+ "[Cd]": 279,
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+ "[Cr+6]": 280,
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+ "[Zr+3]": 281,
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+ "[Rh+]": 282,
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+ "[CH3]": 283,
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+ "[N-3]": 284,
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+ "[Hf+2]": 285,
386
+ "[Th]": 286,
387
+ "[Sb+3]": 287,
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+ "[Cr+2]": 289,
390
+ "[Ru+2]": 290,
391
+ "[Hf+4]": 291,
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+ "[14C]": 292,
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+ "[Ta]": 293,
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+ "[Tl+]": 294,
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+ "[B+]": 295,
396
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397
+ "[PdH2]": 297,
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+ "[Cd+2]": 299,
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+ "[Nb+5]": 302,
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+ "[123I]": 303,
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+ "[c+]": 304,
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+ "[Rb+]": 305,
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+ "[V+2]": 306,
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+ "[CH3+]": 307,
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+ "[Ag+2]": 308,
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+ "[cH+]": 309,
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+ "[Se-]": 311,
412
+ "[As-]": 312,
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+ "[Eu+3]": 313,
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+ "[SH2]": 314,
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+ "[Sm+3]": 315,
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+ "[IH+]": 316,
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418
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419
+ "[PH3]": 319,
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+ "[IH2+]": 320,
421
+ "[SH2+]": 321,
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+ "[Ir+3]": 322,
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+ "[AlH3]": 323,
424
+ "[Sc]": 324,
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+ "[Yb]": 325,
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+ "[15NH2]": 326,
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+ "[Lu]": 327,
428
+ "[sH+]": 328,
429
+ "[Gd]": 329,
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431
+ "[SH3+]": 331,
432
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434
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438
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+ "[GeH]": 339,
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+ "[Sr]": 341,
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+ "[Tl+3]": 342,
443
+ "[Sm+2]": 343,
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446
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+ "[Nd]": 349,
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+ "[Ti+]": 350,
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+ "[IH]": 351,
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+ "[N@+]": 352,
453
+ "[125I]": 353,
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+ "[Eu]": 354,
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+ "[Sn+3]": 355,
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+ "[Er+3]": 357,
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+ "[123I-]": 358,
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461
+ "[SnH2]": 361,
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464
+ "[Pr+3]": 364,
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+ "[Ir+]": 365,
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470
+ "[Tb]": 370,
471
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472
+ "[Mo+4]": 372,
473
+ "[Si+]": 373,
474
+ "[BH]": 374,
475
+ "[Be]": 375,
476
+ "[Rb]": 376,
477
+ "[pH]": 377,
478
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479
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480
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481
+ "[Ir-]": 381,
482
+ "[Be+2]": 382,
483
+ "[C+4]": 383,
484
+ "[RuH2]": 384,
485
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486
+ "[U+2]": 386,
487
+ "[Au-]": 387,
488
+ "%21": 388,
489
+ "%22": 389,
490
+ "[Au+]": 390,
491
+ "[15n]": 391,
492
+ "[Al+2]": 392,
493
+ "[Tb+3]": 393,
494
+ "[15N]": 394,
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+ "[V+3]": 395,
496
+ "[W+6]": 396,
497
+ "[14CH3]": 397,
498
+ "[Cr+4]": 398,
499
+ "[ClH+]": 399,
500
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501
+ "[Ti+6]": 401,
502
+ "[Nd+]": 402,
503
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505
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506
+ "[N@H+]": 406,
507
+ "[RuH]": 407,
508
+ "[Dy+3]": 408,
509
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510
+ "[Hf+3]": 410,
511
+ "[W+4]": 411,
512
+ "[11C]": 412,
513
+ "[13CH]": 413,
514
+ "[Er]": 414,
515
+ "[124I]": 415,
516
+ "[LaH]": 416,
517
+ "[F]": 417,
518
+ "[siH]": 418,
519
+ "[Ga+]": 419,
520
+ "[Cm]": 420,
521
+ "[GeH3]": 421,
522
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523
+ "[U+6]": 423,
524
+ "[SeH+]": 424,
525
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526
+ "[SeH-]": 426,
527
+ "[Pt-]": 427,
528
+ "[Ir+2]": 428,
529
+ "[se+]": 429,
530
+ "[U]": 430,
531
+ "[F+]": 431,
532
+ "[BH2]": 432,
533
+ "[As+]": 433,
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+ "[Cf]": 434,
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+ "[ClH2+]": 435,
536
+ "[Ni+]": 436,
537
+ "[TeH3]": 437,
538
+ "[SbH2]": 438,
539
+ "[Ag+3]": 439,
540
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541
+ "[18O]": 441,
542
+ "[PH4]": 442,
543
+ "[Os+2]": 443,
544
+ "[Na-]": 444,
545
+ "[Sb+2]": 445,
546
+ "[V+4]": 446,
547
+ "[Ho+3]": 447,
548
+ "[68Ga]": 448,
549
+ "[PH-]": 449,
550
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551
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552
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553
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557
+ "[GeH2]": 457,
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+ "[10B]": 458,
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+ "[Mo+2]": 460,
561
+ "[Cr+]": 461,
562
+ "[Pd+4]": 462,
563
+ "[Dy]": 463,
564
+ "[AsH]": 464,
565
+ "[Ba+]": 465,
566
+ "[SeH2]": 466,
567
+ "[In+]": 467,
568
+ "[TeH2]": 468,
569
+ "[BrH+]": 469,
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571
+ "[W+]": 471,
572
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574
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575
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577
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578
+ "[60Co]": 478,
579
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+ "[AsH3]": 480,
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+ "[18OH]": 481,
582
+ "[Ru-2]": 482,
583
+ "[Na-2]": 483,
584
+ "[CuH2]": 484,
585
+ "[31P]": 485,
586
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587
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588
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589
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590
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+ "[131I]": 493,
594
+ "[SH5]": 494,
595
+ "[VH]": 495,
596
+ "[B+2]": 496,
597
+ "[Yb+2]": 497,
598
+ "[14C@H]": 498,
599
+ "[211At]": 499,
600
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601
+ "[IrH]": 501,
602
+ "[IrH2]": 502,
603
+ "[Rh-]": 503,
604
+ "[Cr-]": 504,
605
+ "[Sb+]": 505,
606
+ "[Ni+3]": 506,
607
+ "[TaH3]": 507,
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+ "[64Cu]": 509,
610
+ "[Tc]": 510,
611
+ "[Cd+]": 511,
612
+ "[1H]": 512,
613
+ "[15nH]": 513,
614
+ "[AlH2+]": 514,
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+ "[FH+2]": 515,
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+ "[BiH3]": 516,
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+ "[AsH+]": 519,
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+ "[BaH2]": 520,
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+ "[BaH]": 521,
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+ "[229Th]": 523,
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+ "[Th+4]": 524,
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+ "[As+3]": 525,
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+ "[P@H]": 527,
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629
+ "[7NaH]": 529,
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+ "[Bi+]": 530,
631
+ "[PtH+2]": 531,
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+ "[p-]": 532,
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+ "[Re+5]": 533,
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+ "[NiH]": 534,
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636
+ "[Xe+]": 536,
637
+ "[Ca+]": 537,
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+ "[11c]": 538,
639
+ "[Rh+4]": 539,
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+ "[AcH]": 540,
641
+ "[HeH]": 541,
642
+ "[Sc+2]": 542,
643
+ "[Mn+]": 543,
644
+ "[UH]": 544,
645
+ "[14CH2]": 545,
646
+ "[SiH4+]": 546,
647
+ "[18OH2]": 547,
648
+ "[Ac-]": 548,
649
+ "[Re+4]": 549,
650
+ "[118Sn]": 550,
651
+ "[153Sm]": 551,
652
+ "[P+2]": 552,
653
+ "[9CH]": 553,
654
+ "[9CH3]": 554,
655
+ "[Y-]": 555,
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+ "[NiH2]": 556,
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+ "[Si+2]": 557,
658
+ "[Mn+6]": 558,
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+ "[ZrH2]": 559,
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+ "[C-2]": 560,
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+ "[Bi+5]": 561,
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+ "[24NaH]": 562,
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+ "[Fr]": 563,
664
+ "[15CH]": 564,
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+ "[Se+]": 565,
666
+ "[At]": 566,
667
+ "[P-3]": 567,
668
+ "[124I-]": 568,
669
+ "[CuH2-]": 569,
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+ "[Nb+4]": 570,
671
+ "[Nb+3]": 571,
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+ "[MgH]": 572,
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+ "[Ir+4]": 573,
674
+ "[67Ga+3]": 574,
675
+ "[67Ga]": 575,
676
+ "[13N]": 576,
677
+ "[15OH2]": 577,
678
+ "[2NH]": 578,
679
+ "[Ho]": 579,
680
+ "[Cn]": 580
681
+ },
682
+ "merges": []
683
+ }
684
+ }
tokenizer_config.json ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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vocab.json ADDED
@@ -0,0 +1 @@
 
 
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