Removing eos_token when doing inference. (modelscope#351)

README.md

@@ -62,7 +62,8 @@ Users can check the [documentation of SWIFT](docs/source/GetStarted/快速使用
 
 
 ## 🎉 News
-- 2024.1.26: Support [yi-vl-6b-chat](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm/scripts/yi_vl_6b_chat), yi-vl-34b-chat.
+- 2024.1.29: Support internlm2-math series: internlm2-math-7b, internlm2-math-7b-chat, internlm2-math-20b, internlm2-math-20b-chat.
+- 🔥2024.1.26: Support [yi-vl-6b-chat](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm/scripts/yi_vl_6b_chat), yi-vl-34b-chat.
 - 2024.1.24: Support codefuse-codegeex2-6b-chat, codefuse-qwen-14b-chat.
 - 2024.1.23: Support orion series: orion-14b, [orion-14b-chat](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm/scripts/orion_14b_chat).
 - 2024.1.20: Support [xverse-13b-256k](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm/scripts/xverse_13b_256k), xverse-65b-v2, xverse-65b-chat.
@@ -164,7 +165,7 @@ from swift.llm import (
     infer_main, sft_main, app_ui_main, merge_lora_main
 )
 
-model_type = ModelType.qwen_1_8b_chat
+model_type = ModelType.qwen_1_8b
 sft_args = SftArguments(
     model_type=model_type,
     train_dataset_sample=2000,
@@ -178,7 +179,7 @@ torch.cuda.empty_cache()
 infer_args = InferArguments(
     ckpt_dir=best_model_checkpoint,
     load_dataset_config=True,
-    show_dataset_sample=10)
+    val_dataset_sample=10)
 # merge_lora_main(infer_args)
 result = infer_main(infer_args)
 torch.cuda.empty_cache()
@@ -222,6 +223,8 @@ app_ui_main(infer_args)
     - [deepseek-coder](https://github.com/deepseek-ai/DeepSeek-Coder) series: deepseek-coder-1_3b, deepseek-coder-1_3b-instruct, deepseek-coder-6_7b, deepseek-coder-6_7b-instruct, deepseek-coder-33b, deepseek-coder-33b-instruct.
     - [codegeex2](https://github.com/THUDM/CodeGeeX2) series: codegeex2-6b.
     - [phi](https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of-small-language-models/) series: phi2-3b.
+  - Math:
+    - [internlm2-math](https://github.com/InternLM/InternLM-Math) series: internlm2-math-7b, internlm2-math-7b-chat, internlm2-math-20b, internlm2-math-20b-chat.
 - Supported Datasets: [[Detailed Info]](https://github.com/modelscope/swift/blob/main/docs/source/LLM/%E6%94%AF%E6%8C%81%E7%9A%84%E6%A8%A1%E5%9E%8B%E5%92%8C%E6%95%B0%E6%8D%AE%E9%9B%86.md#%E6%95%B0%E6%8D%AE%E9%9B%86)
   - NLP:
     - General: 🔥alpaca-en(gpt4), 🔥alpaca-zh(gpt4), multi-alpaca-all, instinwild-en, instinwild-zh, cot-en, cot-zh, firefly-all-zh, instruct-en, gpt4all-en, sharegpt-en, sharegpt-zh, tutu-v2-sft-mixture, wikipedia-zh, open-orca, open-orca-gpt4, sharegpt-gpt4.

README_CN.md

@@ -60,6 +60,7 @@ SWIFT（Scalable lightWeight Infrastructure for Fine-Tuning）是一个可扩展
 用户可以查看 [SWIFT官方文档](docs/source/GetStarted/快速使用.md) 来了解详细信息。
 
 ## 🎉 新闻
+- 2024.1.29: 支持internlm2-math系列: internlm2-math-7b, internlm2-math-7b-chat, internlm2-math-20b, internlm2-math-20b-chat.
 - 2024.1.26: 支持[yi-vl-6b-chat](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm/scripts/yi_vl_6b_chat), yi-vl-34b-chat.
 - 2024.1.24: 支持codefuse-codegeex2-6b-chat, codefuse-qwen-14b-chat.
 - 2024.1.23: 支持orion系列: orion-14b, [orion-14b-chat](https://github.com/modelscope/swift/tree/main/examples/pytorch/llm/scripts/orion_14b_chat).
@@ -164,7 +165,7 @@ from swift.llm import (
     infer_main, sft_main, app_ui_main, merge_lora_main
 )
 
-model_type = ModelType.qwen_1_8b_chat
+model_type = ModelType.qwen_1_8b
 sft_args = SftArguments(
     model_type=model_type,
     train_dataset_sample=2000,
@@ -178,7 +179,7 @@ torch.cuda.empty_cache()
 infer_args = InferArguments(
     ckpt_dir=best_model_checkpoint,
     load_dataset_config=True,
-    show_dataset_sample=10)
+    val_dataset_sample=10)
 # merge_lora_main(infer_args)
 result = infer_main(infer_args)
 torch.cuda.empty_cache()
@@ -222,6 +223,8 @@ app_ui_main(infer_args)
     - [deepseek-coder](https://github.com/deepseek-ai/DeepSeek-Coder) 系列: deepseek-coder-1_3b, deepseek-coder-1_3b-instruct, deepseek-coder-6_7b, deepseek-coder-6_7b-instruct, deepseek-coder-33b, deepseek-coder-33b-instruct.
     - [codegeex2](https://github.com/THUDM/CodeGeeX2) 系列: codegeex2-6b.
     - [phi](https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of-small-language-models/) 系列: phi2-3b.
+  - 数学:
+    - [internlm2-math](https://github.com/InternLM/InternLM-Math) 系列: internlm2-math-7b, internlm2-math-7b-chat, internlm2-math-20b, internlm2-math-20b-chat.
 - 支持的数据集: [[详细信息]](https://github.com/modelscope/swift/blob/main/docs/source/LLM/%E6%94%AF%E6%8C%81%E7%9A%84%E6%A8%A1%E5%9E%8B%E5%92%8C%E6%95%B0%E6%8D%AE%E9%9B%86.md#%E6%95%B0%E6%8D%AE%E9%9B%86)
   - NLP:
     - 通用: 🔥alpaca-en(gpt4), 🔥alpaca-zh(gpt4), multi-alpaca-all, instinwild-en, instinwild-zh, cot-en, cot-zh, firefly-all-zh, instruct-en, gpt4all-en, sharegpt-en, sharegpt-zh, tutu-v2-sft-mixture, wikipedia-zh, open-orca, open-orca-gpt4, sharegpt-gpt4.

docs/source/LLM/LLM微调文档.md

@@ -64,7 +64,7 @@ torch.cuda.empty_cache()
 infer_args = InferArguments(
     ckpt_dir=best_model_checkpoint,
     load_dataset_config=True,
-    show_dataset_sample=10)
+    val_dataset_sample=10)
 # merge_lora_main(infer_args)
 result = infer_main(infer_args)
 torch.cuda.empty_cache()

docs/source/LLM/支持的模型和数据集.md

@@ -68,6 +68,10 @@
 |internlm2-20b|[Shanghai_AI_Laboratory/internlm2-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-20b/summary)|wqkv|default-generation-bos|✔|✘||
 |internlm2-20b-sft-chat|[Shanghai_AI_Laboratory/internlm2-chat-20b-sft](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b-sft/summary)|wqkv|internlm2|✔|✘||
 |internlm2-20b-chat|[Shanghai_AI_Laboratory/internlm2-chat-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-chat-20b/summary)|wqkv|internlm2|✔|✘||
+|internlm2-math-7b|[Shanghai_AI_Laboratory/internlm2-math-base-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-base-7b/summary)|wqkv|default-generation-bos|✔|✘||
+|internlm2-math-7b-chat|[Shanghai_AI_Laboratory/internlm2-math-7b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-7b/summary)|wqkv|internlm2|✔|✘||
+|internlm2-math-20b|[Shanghai_AI_Laboratory/internlm2-math-base-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-base-20b/summary)|wqkv|default-generation-bos|✔|✘||
+|internlm2-math-20b-chat|[Shanghai_AI_Laboratory/internlm2-math-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm2-math-20b/summary)|wqkv|internlm2|✔|✘||
 |deepseek-7b|[deepseek-ai/deepseek-llm-7b-base](https://modelscope.cn/models/deepseek-ai/deepseek-llm-7b-base/summary)|q_proj, k_proj, v_proj|default-generation-bos|✔|✔||
 |deepseek-7b-chat|[deepseek-ai/deepseek-llm-7b-chat](https://modelscope.cn/models/deepseek-ai/deepseek-llm-7b-chat/summary)|q_proj, k_proj, v_proj|deepseek|✔|✔||
 |deepseek-moe-16b|[deepseek-ai/deepseek-moe-16b-base](https://modelscope.cn/models/deepseek-ai/deepseek-moe-16b-base/summary)|q_proj, k_proj, v_proj|default-generation-bos|✔|✘||

scripts/utils/run_model_info.py

@@ -56,7 +56,14 @@ def get_model_info_readme_zh(data: List[str]) -> None:
     model_list = []
     for match in match_list:
         model_list += match[2].strip('.').split(',')
-    model_list = [model.strip() for model in model_list]
+    model_list_2 = []
+    for model in model_list:
+        model = model.strip()
+        model_match = re.search(r'\[(.+)\]\(.+\)', model)
+        if model_match is not None:
+            model = model_match.group(1)
+        model_list_2.append(model)
+    model_list = model_list_2
     model_type_list = [d[0] for d in data]
     print(set(model_type_list) - set(model_list))
     print(set(model_list) - set(model_type_list))

swift/llm/utils/model.py

@@ -98,10 +98,10 @@ class ModelType:
     internlm2_20b_sft_chat = 'internlm2-20b-sft-chat'
     internlm2_20b_chat = 'internlm2-20b-chat'
     # internlm2-math
-    internlm2_math_7b_chat = 'internlm2-math-7b-chat'
     internlm2_math_7b = 'internlm2-math-7b'
-    internlm2_math_20b_chat = 'internlm2-math-20b-chat'
+    internlm2_math_7b_chat = 'internlm2-math-7b-chat'
     internlm2_math_20b = 'internlm2-math-20b'
+    internlm2_math_20b_chat = 'internlm2-math-20b-chat'
     # deepseek
     deepseek_7b = 'deepseek-7b'
     deepseek_7b_chat = 'deepseek-7b-chat'

swift/llm/utils/template.py

@@ -86,16 +86,9 @@ def __call__(self, input_ids: Tensor, scores: Tensor) -> bool:
             if isinstance(stop_word, str):
                 if stop_word in text:
                     return True
-            elif isinstance(stop_word, list) and len(stop_word) > 0:
-                res = []
-                for sw in stop_word:
-                    if isinstance(sw, str):
-                        token = getattr(tokenizer, sw)
-                        assert token is not None
-                    else:
-                        token = sw
-                    res.append(token)
-                if input_ids[0].tolist()[-len(res):] == res:
+            else:  # list
+                if len(stop_word) > 0 and input_ids[0].tolist(
+                )[-len(stop_word):] == stop_word:
                     return True
         return False
 
@@ -132,6 +125,24 @@ def __init__(self,
         self.use_default_system = True
         self._is_init = False
 
+    @staticmethod
+    def _preprocess_prompt(tokenizer: PreTrainedTokenizerBase,
+                           value: Optional[Prompt]) -> Optional[Prompt]:
+        # e.g. [['eos_token_id']] -> [[2]]
+        if value is None:
+            return None
+        res_value = []
+        for v in value:
+            if isinstance(v, list):
+                res_v = []
+                for sub_v in v:
+                    if isinstance(sub_v, str):
+                        sub_v = getattr(tokenizer, sub_v)
+                    res_v.append(sub_v)
+                v = res_v
+            res_value.append(v)
+        return res_value
+
     def _init_template(self,
                        tokenizer: PreTrainedTokenizerBase,
                        default_system: Optional[str] = None,
@@ -148,6 +159,10 @@ def _init_template(self,
         self.max_length = max_length
         self.truncation_strategy = truncation_strategy
         self.model = kwargs.get('model', None)
+        for key in ['prefix', 'prompt', 'chat_sep', 'suffix']:
+            value = getattr(self, key)
+            value = self._preprocess_prompt(tokenizer, value)
+            setattr(self, key, value)
 
     def encode(
             self, example: Dict[str,
@@ -254,14 +269,7 @@ def _encode_context_list(
                     add_special_tokens=False,
                     **curr_tokenizer_kwargs)['input_ids']
             else:
-                token_list = []
-                for c in context:
-                    if isinstance(c, str):
-                        token = getattr(tokenizer, c)
-                        assert token is not None
-                    else:
-                        token = c
-                    token_list.append(token)
+                token_list = context
             input_ids += token_list
             if i in compute_loss_idx:
                 labels += token_list

swift/llm/utils/utils.py

@@ -441,6 +441,8 @@ def inference_stream(model: PreTrainedModel,
         stream_config.eos_token_id = tokenizer.eos_token_id
     if tokenizer.pad_token_id is not None:
         stream_config.pad_token_id = tokenizer.pad_token_id
+    if tokenizer.bos_token_id is not None:
+        stream_config.bos_token_id = tokenizer.bos_token_id
     if stream_config.max_new_tokens is not None:
         stream_config.max_length = 20  # fix max_length, max_new_tokens warning
     stream_config.do_sample = True  # avoid is_greedy_gen_mode = True
@@ -568,6 +570,8 @@ def inference(model: PreTrainedModel,
         generation_config.eos_token_id = tokenizer.eos_token_id
     if tokenizer.pad_token_id is not None:
         generation_config.pad_token_id = tokenizer.pad_token_id
+    if tokenizer.bos_token_id is not None:
+        generation_config.bos_token_id = tokenizer.bos_token_id
     if generation_config.max_new_tokens is not None:
         generation_config.max_length = 20  # fix max_length, max_new_tokens warning
     if template.suffix[-1] not in stop_words:

tests/llm/test_run.py

@@ -251,7 +251,9 @@ def test_cogagent_instruct(self):
         torch.cuda.empty_cache()
         infer_main(
             InferArguments(
-                ckpt_dir=best_model_checkpoint, load_dataset_config=True))
+                ckpt_dir=best_model_checkpoint,
+                load_dataset_config=True,
+                val_dataset_sample=2))
 
     def test_yi_vl_6b_chat(self):
         if not __name__ == '__main__':
@@ -272,7 +274,9 @@ def test_yi_vl_6b_chat(self):
         torch.cuda.empty_cache()
         infer_main(
             InferArguments(
-                ckpt_dir=best_model_checkpoint, load_dataset_config=True))
+                ckpt_dir=best_model_checkpoint,
+                load_dataset_config=True,
+                val_dataset_sample=2))
 
     def test_dpo(self):
         if not __name__ == '__main__':
@@ -288,7 +292,9 @@ def test_dpo(self):
         torch.cuda.empty_cache()
         infer_main(
             InferArguments(
-                ckpt_dir=best_model_checkpoint, load_dataset_config=True))
+                ckpt_dir=best_model_checkpoint,
+                load_dataset_config=True,
+                val_dataset_sample=2))
 
 
 def data_collate_fn(batch: List[Dict[str, Any]],