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LICENSE

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+Tongyi Qianwen LICENSE AGREEMENT
+
+Tongyi Qianwen Release Date: August 3, 2023
+
+By clicking to agree or by using or distributing any portion or element of the Tongyi Qianwen Materials, you will be deemed to have recognized and accepted the content of this Agreement, which is effective immediately.
+
+1. Definitions
+    a. This Tongyi Qianwen LICENSE AGREEMENT (this "Agreement") shall mean the terms and conditions for use, reproduction, distribution and modification of the Materials as defined by this Agreement.
+    b. "We"(or "Us") shall mean Alibaba Cloud.
+    c. "You" (or "Your") shall mean a natural person or legal entity exercising the rights granted by this Agreement and/or using the Materials for any purpose and in any field of use.
+    d. "Third Parties" shall mean individuals or legal entities that are not under common control with Us or You.
+    e. "Tongyi Qianwen" shall mean the large language models (including Qwen-7B model and Qwen-7B-Chat model), and software and algorithms, consisting of trained model weights, parameters (including optimizer states), machine-learning model code, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Us.
+    f. "Materials" shall mean, collectively, Alibaba Cloud's proprietary Tongyi Qianwen and Documentation (and any portion thereof) made available under this Agreement.
+    g. "Source" form shall mean the preferred form for making modifications, including but not limited to model source code, documentation source, and configuration files.
+    h. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation,
+ and conversions to other media types.
+
+2. Grant of Rights
+You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Alibaba Cloud's intellectual property or other rights owned by Us embodied in the Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Materials.
+
+3. Redistribution
+You may reproduce and distribute copies of the Materials or derivative works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions:
+    a. You shall give any other recipients of the Materials or derivative works a copy of this Agreement;
+    b. You shall cause any modified files to carry prominent notices stating that You changed the files;
+    c. You shall retain in all copies of the Materials that You distribute the following attribution notices within a "Notice" text file distributed as a part of such copies: "Tongyi Qianwen is licensed under the Tongyi Qianwen LICENSE AGREEMENT, Copyright (c) Alibaba Cloud. All Rights Reserved."; and
+    d. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such derivative works as a whole, provided Your use, reproduction, and distribution of the work otherwise complies with the terms and conditions of this Agreement.
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+4. Restrictions
+If you are commercially using the Materials, and your product or service has more than 100 million monthly active users, You shall request a license from Us. You cannot exercise your rights under this Agreement without our express authorization.
+
+5. Rules of use
+    a. The Materials may be subject to export controls or restrictions in China, the United States or other countries or regions. You shall comply with applicable laws and regulations in your use of the Materials.
+    b. You can not use the Materials or any output therefrom to improve any other large language model (excluding Tongyi Qianwen or derivative works thereof).
+
+6. Intellectual Property
+    a. We retain ownership of all intellectual property rights in and to the Materials and derivatives made by or for Us. Conditioned upon compliance with the terms and conditions of this Agreement, with respect to any derivative works and modifications of the Materials that are made by you, you are and will be the owner of such derivative works and modifications.
+    b. No trademark license is granted to use the trade names, trademarks, service marks, or product names of Us, except as required to fulfill notice requirements under this Agreement or as required for reasonable and customary use in describing and redistributing the Materials.
+    c. If you commence a lawsuit or other proceedings (including a cross-claim or counterclaim in a lawsuit) against Us or any entity alleging that the Materials or any output therefrom, or any part of the foregoing, infringe any intellectual property or other right owned or licensable by you, then all licences granted to you under this Agreement shall terminate as of the date such lawsuit or other proceeding is commenced or brought.
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+7. Disclaimer of Warranty and Limitation of Liability
+
+    a. We are not obligated to support, update, provide training for, or develop any further version of the Tongyi Qianwen Materials or to grant any license thereto.
+    b. THE MATERIALS ARE PROVIDED "AS IS" WITHOUT ANY EXPRESS OR IMPLIED WARRANTY OF ANY KIND INCLUDING WARRANTIES OF MERCHANTABILITY, NONINFRINGEMENT, OR FITNESS FOR A PARTICULAR PURPOSE. WE MAKE NO WARRANTY AND ASSUME NO RESPONSIBILITY FOR THE SAFETY OR STABILITY OF THE MATERIALS AND ANY OUTPUT THEREFROM.
+    c. IN NO EVENT SHALL WE BE LIABLE TO YOU FOR ANY DAMAGES, INCLUDING, BUT NOT LIMITED TO ANY DIRECT, OR INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES ARISING FROM YOUR USE OR INABILITY TO USE THE MATERIALS OR ANY OUTPUT OF IT, NO MATTER HOW IT’S CAUSED.
+    d. You will defend, indemnify and hold harmless Us from and against any claim by any third party arising out of or related to your use or distribution of the Materials.
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+8. Survival and Termination.
+    a. The term of this Agreement shall commence upon your acceptance of this Agreement or access to the Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein.
+    b. We may terminate this Agreement if you breach any of the terms or conditions of this Agreement. Upon termination of this Agreement, you must delete and cease use of the Materials. Sections 7 and 9 shall survive the termination of this Agreement.
+
+9. Governing Law and Jurisdiction.
+    a. This Agreement and any dispute arising out of or relating to it will be governed by the laws of China, without regard to conflict of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement.
+    b. The People's Courts in Hangzhou City shall have exclusive jurisdiction over any dispute arising out of this Agreement.

NOTICE

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+------------- LICENSE FOR NVIDIA Megatron-LM code  --------------
+
+Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions
+are met:
+  * Redistributions of source code must retain the above copyright
+    notice, this list of conditions and the following disclaimer.
+  * Redistributions in binary form must reproduce the above copyright
+    notice, this list of conditions and the following disclaimer in the
+    documentation and/or other materials provided with the distribution.
+  * Neither the name of NVIDIA CORPORATION nor the names of its
+    contributors may be used to endorse or promote products derived
+    from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
+EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
+CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
+OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+------------- LICENSE FOR OpenAI tiktoken code  --------------
+
+MIT License
+
+Copyright (c) 2022 OpenAI, Shantanu Jain
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

config.json

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+{
+  "_name_or_path": "/notebooks/qwen",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 6144,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.32.0.dev0",
+  "use_cache": true,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "chat_format": "chatml",
+  "decay_bound": 0.0,
+  "decay_factor": 1.0,
+  "eos_token_id": 151643,
+  "factual_nucleus_sampling": false,
+  "max_context_size": 1024,
+  "max_generate_size": 512,
+  "max_new_tokens": 512,
+  "pad_token_id": 151643,
+  "stop_words_ids": [[151643]],
+  "do_sample": true,
+  "top_k": 0,
+  "top_p": 0.8,
+  "transformers_version": "4.31.0"
+}

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+  }
+}

tokenization_qwen.py

@@ -0,0 +1,258 @@
+# Copyright (c) Alibaba Cloud.
+#
+# This source code is licensed under the license found in the
+# LICENSE file in the root directory of this source tree.
+
+"""Tokenization classes for QWen."""
+
+from __future__ import absolute_import, division, print_function, unicode_literals
+
+import json
+import logging
+import os
+import unicodedata
+from io import open
+import base64
+import tiktoken
+from typing import List, Optional, Tuple, Union
+
+from transformers import PreTrainedTokenizer, AddedToken
+
+logger = logging.getLogger(__name__)
+
+VOCAB_FILES_NAMES = {"vocab_file": "qwen.tiktoken"}
+
+
+class QWenTokenizer(PreTrainedTokenizer):
+    """QWen tokenizer."""
+
+    """NOTE: This tokenizer will not handle special tokens to avoid injection attacks"""
+
+    vocab_files_names = VOCAB_FILES_NAMES
+
+    def __init__(
+        self,
+        vocab_file,
+        errors="replace",
+        max_len=None,
+        unk_token="<|endoftext|>",
+        bos_token="<|endoftext|>",
+        eos_token="<|endoftext|>",
+        pad_token=None,
+        add_prefix_space=False,
+        add_bos_token=False,
+        add_more_sp_tokens=True,
+        **kwargs,
+    ):
+        bos_token = (
+            AddedToken(bos_token, lstrip=False, rstrip=False)
+            if isinstance(bos_token, str)
+            else bos_token
+        )
+        eos_token = (
+            AddedToken(eos_token, lstrip=False, rstrip=False)
+            if isinstance(eos_token, str)
+            else eos_token
+        )
+        unk_token = (
+            AddedToken(unk_token, lstrip=False, rstrip=False)
+            if isinstance(unk_token, str)
+            else unk_token
+        )
+        pad_token = (
+            AddedToken(pad_token, lstrip=False, rstrip=False)
+            if isinstance(pad_token, str)
+            else pad_token
+        )
+        super().__init__(
+            errors=errors,
+            unk_token=unk_token,
+            bos_token=bos_token,
+            eos_token=eos_token,
+            pad_token=pad_token,
+            add_prefix_space=add_prefix_space,
+            add_bos_token=add_bos_token,
+        )
+        self.add_bos_token = add_bos_token
+        self.max_len = max_len if max_len is not None else int(1e12)
+
+        self.errors = errors  # how to handle errors in decoding
+
+        name = "Qwen"
+        ENDOFTEXT = "<|endoftext|>"
+        IMSTART = "<|im_start|>"
+        IMEND = "<|im_end|>"
+        if add_more_sp_tokens:
+            special_tokens = (
+                ENDOFTEXT,
+                IMSTART,
+                IMEND,
+                "<R>",
+                "<S>",
+                "<X>",
+                "<mask>",
+                "<sep>",
+            ) + tuple([f"<extra_{i}>" for i in range(200)])
+        else:
+            special_tokens = (ENDOFTEXT, IMSTART, IMEND)
+
+        PAT_STR = r"""(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+"""
+
+        def load_tiktoken_bpe(tiktoken_bpe_file: str) -> "dict[bytes, int]":
+            contents = open(tiktoken_bpe_file, "rb").read()
+            return {
+                base64.b64decode(token): int(rank)
+                for token, rank in (
+                    line.split() for line in contents.splitlines() if line
+                )
+            }
+
+        mergeable_ranks = load_tiktoken_bpe(vocab_file)
+        special_tokens = {
+            token: index
+            for index, token in enumerate(special_tokens, start=len(mergeable_ranks))
+        }
+        self.special_tokens = special_tokens
+        enc = tiktoken.Encoding(
+            name,
+            pat_str=PAT_STR,
+            mergeable_ranks=mergeable_ranks,
+            special_tokens=special_tokens,
+        )
+        assert (
+            len(mergeable_ranks) + len(special_tokens) == enc.n_vocab
+        ), f"{len(mergeable_ranks) + len(special_tokens)} != {enc.n_vocab} in encoding"
+
+        self.mergeable_ranks = mergeable_ranks
+        self.encoder = self.mergeable_ranks
+        self.decoder = {v: k for k, v in self.encoder.items()}
+        self.tokenizer = enc  # type: tiktoken.Encoding
+        self.eod_id = self.tokenizer.eot_token
+        self.im_start_id = special_tokens[IMSTART]
+        self.im_end_id = special_tokens[IMEND]
+
+    def __len__(self):
+        return self.tokenizer.n_vocab
+
+    def get_vocab(self):
+        return self.mergeable_ranks
+
+    def convert_tokens_to_ids(self, tokens):
+        ids = []
+        # Remove support for py2
+        if isinstance(tokens, str):
+            if tokens in self.special_tokens:
+                return self.special_tokens[tokens]
+            else:
+                return self.encoder.get(tokens)
+        for token in tokens:
+            if token in self.special_tokens:
+                ids.append(self.special_tokens[token])
+            else:
+                ids.append(self.encoder.get(token))
+        if len(ids) > self.max_len:
+            logger.warning(
+                "Token indices sequence length is longer than the specified maximum "
+                " sequence length for this model ({} > {}). Running this"
+                " sequence through the model will result in indexing errors".format(
+                    len(ids), self.max_len
+                )
+            )
+        return ids
+
+    def save_vocabulary(self, save_directory: str, **kwargs) -> Tuple[str]:
+        """
+        Save only the vocabulary of the tokenizer (vocabulary + added tokens).
+
+        Returns:
+            `Tuple(str)`: Paths to the files saved.
+        """
+        file_path = os.path.join(save_directory, "qwen.tiktoken")
+        with open(file_path, "w", encoding="utf8") as w:
+            for k, v in self.mergeable_ranks.items():
+                line = base64.b64encode(k).decode("utf8") + " " + str(v) + "\n"
+                w.write(line)
+        return (file_path,)
+
+    def tokenize(self, text: str, **kwargs) -> List[str]:
+        """
+        Converts a string in a sequence of tokens, replacing unknown tokens with the `unk_token`.
+
+        Args:
+            text (`str`):
+                The sequence to be encoded.
+            kwargs (additional keyword arguments, *optional*):
+                Will be passed to the underlying model specific encode method. See details in
+                [`~PreTrainedTokenizerBase.__call__`]
+
+        Returns:
+            `List[str]`: The list of tokens.
+        """
+        tokens = []
+        text = unicodedata.normalize("NFC", text)
+        for t in self.tokenizer.encode_ordinary(text):
+            tokens.append(self.decoder[t])
+        return tokens
+
+    def convert_tokens_to_string(self, tokens: List[str]) -> str:
+        """
+        Converts a sequence of tokens in a single string. The most simple way to do it is `" ".join(tokens)` but we
+        often want to remove sub-word tokenization artifacts at the same time.
+        """
+        text = "".join(tokens)
+        text = bytearray([self.byte_decoder[c] for c in text]).decode(
+            "utf-8", errors=self.errors
+        )
+        return text
+
+    @property
+    def vocab_size(self):
+        return self.tokenizer.n_vocab
+
+    def _convert_id_to_token(self, index: int) -> str:
+        if index >= self.tokenizer.n_vocab:
+            return self.unk_token
+        return self.tokenizer.decode([index])
+
+    def _convert_token_to_id(self, token: str) -> int:
+        """Converts a token to an id using the vocab."""
+        return self.encoder.get(token.encode('UTF-8'), self.tokenizer.encode(self.unk_token, allowed_special='all')[0])
+
+    @property
+    def all_special_tokens(self) -> List[str]:
+        """
+        `List[str]`: All the special tokens (`'<unk>'`, `'<cls>'`, etc.) mapped to class attributes.
+
+        Convert tokens of `tokenizers.AddedToken` type to string.
+        """
+        all_toks = [str(s) for s in self.special_tokens.keys()]
+        return all_toks
+
+    @property
+    def all_special_ids(self) -> List[int]:
+        """
+        `List[int]`: List the ids of the special tokens(`'<unk>'`, `'<cls>'`, etc.) mapped to class attributes.
+        """
+        all_ids = [v for v in self.special_tokens.values()]
+        return all_ids
+
+    def _tokenize(self, text, **kwargs):
+        """
+        Converts a string in a sequence of tokens (string), using the tokenizer. Split in words for word-based
+        vocabulary or sub-words for sub-word-based vocabularies (BPE/SentencePieces/WordPieces).
+
+        Do NOT take care of added tokens.
+        """
+        raise NotImplementedError
+
+    def _decode(
+        self,
+        token_ids: Union[int, List[int]],
+        skip_special_tokens: bool = False,
+        **kwargs,
+    ) -> str:
+        if isinstance(token_ids, int):
+            token_ids = [token_ids]
+        if skip_special_tokens:
+            token_ids = [i for i in token_ids if i not in self.all_special_ids]
+        return self.tokenizer.decode(token_ids)

tokenizer_config.json

@@ -0,0 +1,11 @@
+{
+  "remove_space": false,
+  "do_lower_case": false,
+  "tokenizer_class": "QWenTokenizer",
+  "auto_map": {
+    "AutoTokenizer": [
+      "tokenization_qwen.QWenTokenizer",
+      null
+      ]
+  }
+}