Minor fixes
Browse files- README.md +0 -1
- modeling_m5_encoder.py +2 -1
README.md
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@@ -46,7 +46,6 @@ Inputs require SELFIES tokenization **and** a precomputed distance matrix
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(`relative_position`). Use the helper bundled in the repo:
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```python
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-
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tokenizer = AutoTokenizer.from_pretrained("IlPakoZ/m5-encoder", trust_remote_code=True)
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smiles = "CCO"
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(`relative_position`). Use the helper bundled in the repo:
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```python
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tokenizer = AutoTokenizer.from_pretrained("IlPakoZ/m5-encoder", trust_remote_code=True)
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smiles = "CCO"
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modeling_m5_encoder.py
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@@ -36,6 +36,7 @@ class M5EncoderConfig(T5Config):
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relative_attention_max_distance=128,
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relative_attention_num_buckets=48,
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vocab_size=1032,
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**kwargs,
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):
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super().__init__(d_ff=d_ff,
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@@ -50,7 +51,7 @@ class M5EncoderConfig(T5Config):
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relative_attention_max_distance=relative_attention_max_distance,
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relative_attention_num_buckets=relative_attention_num_buckets,
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vocab_size=vocab_size,
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-
num_decoder_layers=
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**kwargs)
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class M5Encoder(PreTrainedModel):
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relative_attention_max_distance=128,
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relative_attention_num_buckets=48,
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vocab_size=1032,
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+
num_decoder_layers=0,
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**kwargs,
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):
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super().__init__(d_ff=d_ff,
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relative_attention_max_distance=relative_attention_max_distance,
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relative_attention_num_buckets=relative_attention_num_buckets,
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vocab_size=vocab_size,
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+
num_decoder_layers=num_decoder_layers,
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**kwargs)
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class M5Encoder(PreTrainedModel):
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