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convert : fix set_vocab_sentencepiece (#6866)
* convert : fix set_vocab_sentencepiece * Update convert-hf-to-gguf.py
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@ -573,6 +573,10 @@ class Model:
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vocab_size = self.hparams.get('vocab_size', tokenizer.vocab_size())
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tokens: list[bytes] = [f"[PAD{i}]".encode("utf-8") for i in range(vocab_size)]
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scores: list[float] = [-10000.0] * vocab_size
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toktypes: list[int] = [SentencePieceTokenTypes.UNKNOWN] * vocab_size
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for token_id in range(tokenizer.vocab_size()):
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piece = tokenizer.IdToPiece(token_id)
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text = piece.encode("utf-8")
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@ -588,21 +592,23 @@ class Model:
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elif tokenizer.IsByte(token_id):
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toktype = SentencePieceTokenTypes.BYTE
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tokens.append(text)
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scores.append(score)
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toktypes.append(toktype)
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tokens[token_id] = text
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scores[token_id] = score
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toktypes[token_id] = toktype
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added_tokens_file = self.dir_model / 'added_tokens.json'
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if added_tokens_file.is_file():
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with open(added_tokens_file, "r", encoding="utf-8") as f:
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added_tokens_json = json.load(f)
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for key in added_tokens_json:
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key = key.encode("utf-8")
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if key not in tokens:
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tokens.append(key)
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scores.append(-1000.0)
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toktypes.append(SentencePieceTokenTypes.USER_DEFINED)
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token_id = added_tokens_json[key]
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if (token_id >= vocab_size):
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logger.warning(f'ignore token {token_id}: id is out of range, max={vocab_size - 1}')
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continue
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tokens[token_id] = key.encode("utf-8")
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scores[token_id] = -1000.0
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toktypes[token_id] = SentencePieceTokenTypes.USER_DEFINED
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if vocab_size > len(tokens):
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pad_count = vocab_size - len(tokens)
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@ -612,8 +618,6 @@ class Model:
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scores.append(-1000.0)
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toktypes.append(SentencePieceTokenTypes.UNUSED)
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assert len(tokens) == vocab_size
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self.gguf_writer.add_tokenizer_model("llama")
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self.gguf_writer.add_tokenizer_pre("default")
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self.gguf_writer.add_token_list(tokens)
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