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LICENSE

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README.md

@@ -0,0 +1,60 @@
+---
+license: apache-2.0
+language:
+- en
+---
+## Empowering Character-level Text Infilling by Eliminating Sub-Tokens
+
+<p align="center">
+    <a href="https://arxiv.org/abs/2405.17103">📄 Paper</a> •
+    <a href="https://github.com/SenseLLM/FIM-SE">🏠 Repo</a> •
+    <a href="https://huggingface.co/SenseLLM/FIM-SE-CL-13B">🤖 Models</a>
+</p>
+
+## Introduction
+FIM-SE stands for Fill-In-the-Middle with both Starting and Ending character constraints. The proposed method addresses character-level infilling tasks by utilizing a line-level format to avoid predicting any sub-token in inference.
+
+![](method.png)
+
+<hr>
+
+## Models
+
+| Model | Checkpoint | Size | License|
+|:------|:-----------|:-----|:-------|
+| FIM-SE-CL-7B   | 🤗 [HF Link](https://huggingface.co/SenseLLM/FIM-SE-CL-7B)  | 7B  | [Llama2](https://ai.meta.com/llama/license/) |
+| FIM-SE-CL-34B  | 🤗 [HF Link](https://huggingface.co/SenseLLM/FIM-SE-CL-34B) | 13B | [Llama2](https://ai.meta.com/llama/license/) |
+| FIM-SE-SC-1B   | 🤗 [HF Link](https://huggingface.co/SenseLLM/FIM-SE-SC-1B)  | 1B  | [StarCoder](https://github.com/bigcode-project/starcoder/blob/main/LICENSE) |
+| FIM-SE-SC-15B  | 🤗 [HF Link](https://huggingface.co/SenseLLM/FIM-SE-SC-15B) | 15B | [StarCoder](https://github.com/bigcode-project/starcoder/blob/main/LICENSE) |
+
+## How to Use
+
+#### Prompt Format
+
+As shown in the figure, the prompt is organized as
+```text
+<PRE>R-Prefix<SUF>R-Suffix<START>L-Prefix<END>F-Suffix<MID>
+```
+
+#### Inference Code
+Please refer to our [GitHub Repo](https://github.com/SenseLLM/FIM-SE) for more technical details.
+
+## Citation
+
+If you find this repo useful for your research, please kindly cite our paper:
+```
+@misc{ren2024empowering,
+    title={Empowering Character-level Text Infilling by Eliminating Sub-Tokens}, 
+    author={Houxing Ren and Mingjie Zhan and Zhongyuan Wu and Hongsheng Li},
+    year={2024},
+    eprint={2405.17103},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+## Acknowledgments
+
+We thank the following amazing projects that truly inspired us:
+
+- [FIM](https://arxiv.org/abs/2207.14255)

added_tokens.json

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+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.36.1",
+  "use_cache": false,
+  "vocab_size": 32128
+}

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+    "<EOT>",
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenization_llama.py

@@ -0,0 +1,111 @@
+from typing import List
+
+from transformers import (
+    LlamaTokenizer,
+    LlamaTokenizerFast,
+    SLOW_TO_FAST_CONVERTERS,
+)
+
+from tokenizers import decoders, normalizers
+from transformers.convert_slow_tokenizer import LlamaConverter
+
+SPIECE_UNDERLINE = "▁"
+
+class FixLlamaTokenizer(LlamaTokenizer):
+
+    def __init__(self, *args, **kwargs):
+        kwargs['legacy'] = False
+        super().__init__(*args, **kwargs)
+
+    def tokenize(self, text, **kwargs) -> List[int]:
+        
+        return super().tokenize(text.replace(SPIECE_UNDERLINE, " "), **kwargs)
+
+    def _tokenize(self, text, **kwargs):
+        return self.sp_model.encode(text, out_type=str)
+
+    def convert_tokens_to_string(self, tokens):
+        """Converts a sequence of tokens (string) in a single string."""
+
+        current_sub_tokens = []
+        out_string = ""
+        for _, token in enumerate(tokens):
+            # make sure that special tokens are not decoded using sentencepiece model
+            if token in self.all_special_tokens:
+                out_string += self.sp_model.decode(current_sub_tokens) + token
+                current_sub_tokens = []
+            else:
+                current_sub_tokens.append(token)
+        out_string += self.sp_model.decode(current_sub_tokens)
+        return out_string
+
+    def _decode(
+        self,
+        token_ids: List[int],
+        skip_special_tokens: bool = False,
+        clean_up_tokenization_spaces: bool = None,
+        spaces_between_special_tokens: bool = False,
+        **kwargs,
+    ) -> str:
+        self._decode_use_source_tokenizer = kwargs.pop("use_source_tokenizer", False)
+
+        filtered_tokens = self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens)
+        legacy_added_tokens = set(self._added_tokens_encoder.keys()) - set(self.all_special_tokens) | {
+            token for token in self.additional_special_tokens if self.convert_tokens_to_ids(token) >= self.vocab_size
+        }
+        # To avoid mixing byte-level and unicode for byte-level BPT
+        # we need to build string separately for added tokens and byte-level tokens
+        # cf. https://github.com/huggingface/transformers/issues/1133
+        sub_texts = []
+        current_sub_text = []
+        # TODO @ArthurZ in version 5, special tokens should be handled in convert_tokens_to_string, while _convert_tokens_to_string
+        for token in filtered_tokens:
+            if skip_special_tokens and token in self.all_special_ids:
+                continue
+            if token in legacy_added_tokens:
+                if current_sub_text:
+                    string = self.convert_tokens_to_string(current_sub_text)
+                    if len(string) > 0:
+                        sub_texts.append(string)
+                    current_sub_text = []
+                sub_texts.append(token)
+            else:
+                current_sub_text.append(token)
+        if current_sub_text:
+            sub_texts.append(self.convert_tokens_to_string(current_sub_text))
+
+        if spaces_between_special_tokens:
+            text = " ".join(sub_texts)
+        else:
+            text = "".join(sub_texts)
+
+        clean_up_tokenization_spaces = (
+            clean_up_tokenization_spaces
+            if clean_up_tokenization_spaces is not None
+            else self.clean_up_tokenization_spaces
+        )
+        if clean_up_tokenization_spaces:
+            clean_text = self.clean_up_tokenization(text)
+            return clean_text
+        else:
+            return text
+
+class FixLlamaTokenizerFast(LlamaTokenizerFast):
+    slow_tokenizer_class = FixLlamaTokenizer
+
+class FixLlamaTokenizerConverter(LlamaConverter):
+    def normalizer(self, proto):
+        return normalizers.Replace(pattern=' ', content='▁')
+
+    def decoder(self, replacement, add_prefix_space):
+        return decoders.Sequence(
+            [
+                decoders.Replace('▁', ' '),
+                decoders.ByteFallback(),
+                decoders.Fuse(),
+            ]
+        )
+
+FixLlamaTokenizer.register_for_auto_class()
+FixLlamaTokenizerFast.register_for_auto_class()
+SLOW_TO_FAST_CONVERTERS[FixLlamaTokenizer.__name__] = FixLlamaTokenizerConverter

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5caa1a2666db23571a791ba47d0f97cf02e21328cbc6b4571a562436a4cb22a3
+size 500010

tokenizer_config.json

@@ -0,0 +1,103 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32007": {
+      "content": "<PRE>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32008": {
+      "content": "<SUF>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32009": {
+      "content": "<MID>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32010": {
+      "content": "<EOT>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32016": {
+      "content": "<START>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32017": {
+      "content": "<END>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<PRE>",
+    "<MID>",
+    "<SUF>",
+    "<EOT>",
+    "<START>",
+    "<END>"
+  ],
+  "auto_map": {
+    "AutoTokenizer": [
+      "tokenization_llama.FixLlamaTokenizer",
+      "tokenization_llama.FixLlamaTokenizerFast"
+    ]
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "FixLlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}