Fill-Mask
Transformers
Safetensors
modernbert
chemistry
molecules
selfies
ape-tokenizer
masked-language-modeling
Instructions to use HauserGroup/ModernMolBERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HauserGroup/ModernMolBERT-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="HauserGroup/ModernMolBERT-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("HauserGroup/ModernMolBERT-small") model = AutoModelForMaskedLM.from_pretrained("HauserGroup/ModernMolBERT-small") - Notebooks
- Google Colab
- Kaggle
File size: 1,536 Bytes
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"output_dir": "runs/chembl36_small_mask_mlm_lr_sweep/mask_standard__mlm_0p15__lr_4e-4",
"tokenizer_vocab_path": "tokenizer/chembl36_selfies_2m_ape_max2_min3000.json",
"tokenizer_metadata_path": "tokenizer/chembl36_selfies_2m_ape_max2_min3000.metadata.json",
"dataset_name": "data/pretrain/chembl36_selfies",
"selfies_column": "selfies",
"train_split": "train",
"validation_split": "valid",
"use_validation_split": true,
"data_dir": null,
"data_files": null,
"eval_size": 4096,
"shuffle_buffer_size": 100000,
"seed": 42,
"val_split_mod": 100,
"val_split_bucket": 0,
"tokenizer_validation_samples": 1000,
"unk_rate_threshold": 0.001,
"truncation_warn_threshold": 0.05,
"model_size": "small",
"max_seq_length": 128,
"mlm_probability": 0.15,
"masking_strategy": "standard",
"span_p_geom": 0.4,
"span_max_length": 6,
"heteroatom_start_weight": 2.0,
"max_steps": 30000,
"per_device_train_batch_size": 256,
"per_device_eval_batch_size": 256,
"gradient_accumulation_steps": 1,
"learning_rate": 0.0004,
"weight_decay": 0.01,
"warmup_steps": 1500,
"max_grad_norm": 1.0,
"load_best_model_at_end": true,
"metric_for_best_model": "eval_loss",
"greater_is_better": false,
"logging_steps": 100,
"eval_steps": 5000,
"save_steps": 5000,
"save_total_limit": 2,
"device_backend": "cuda",
"bf16": true,
"fp16": false,
"num_workers": 4,
"max_eval_batches": 16,
"report_to": "tensorboard",
"compute_masked_accuracy": true,
"debug": false,
"hf_login": false
} |