初始化项目，由ModelHub XC社区提供模型
Model: swift/QwenLong-L1-32B-AWQ Source: Original Platform
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README.md
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---
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license: Apache License 2.0
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tasks:
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- text-generation
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base_model:
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- iic/QwenLong-L1-32B
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---
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## Intro
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The AWQ version is quantized using [ms-swift](https://github.com/modelscope/ms-swift). Note that the AWQ version for QwenLong-L1-32B models are verified to be working on Transformers/vLLM. We have not have the chance to tested them on other engines.
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## Inference
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```python
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from modelscope import AutoModelForCausalLM, AutoTokenizer
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model_name = "swift/QwenLong-L1-32B-AWQ"
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# load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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# prepare the model input
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template = """Please read the following text and answer the question below.
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<text>
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$DOC$
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</text>
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$Q$
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Format your response as follows: "Therefore, the answer is (insert answer here)"."""
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context = "<YOUR_CONTEXT_HERE>"
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question = "<YOUR_QUESTION_HERE>"
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prompt = template.replace('$DOC$', context.strip()).replace('$Q$', question.strip())
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messages = [
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{"role": "user", "content": prompt}
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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# conduct text completion
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=10000,
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temperature=0.7,
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top_p=0.95
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)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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# parsing thinking content
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try:
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# rindex finding 151649 (</think>)
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index = len(output_ids) - output_ids[::-1].index(151649)
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except ValueError:
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index = 0
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thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n")
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content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n")
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print("thinking content:", thinking_content)
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print("content:", content)
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```
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## Quantization
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The model has undergone AWQ int4 quantization using the [ms-swift](https://github.com/modelscope/ms-swift) framework.
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If you have fine-tuned the model and wish to quantize the fine-tuned version, you can refer to the following quantization scripts:
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- Dense Model Quantization Script: [View Here](https://github.com/modelscope/ms-swift/blob/main/examples/export/quantize/awq.sh)
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- MoE Model Quantization Script: [View Here](https://github.com/modelscope/ms-swift/blob/main/examples/export/quantize/moe/awq.sh)
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With these scripts, you can easily complete the quantization process for the model.
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151646,
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"eos_token_id": 151643,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 27648,
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"max_position_embeddings": 131072,
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"max_window_layers": 64,
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"model_type": "qwen2",
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"num_attention_heads": 40,
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"num_hidden_layers": 64,
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"num_key_value_heads": 8,
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"pad_token_id": 151643,
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"quantization_config": {
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"bits": 4,
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"group_size": 128,
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"modules_to_not_convert": null,
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"quant_method": "awq",
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"version": "gemm",
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"zero_point": true
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},
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.51.3",
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"use_cache": false,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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configuration.json
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{"framework":"Pytorch","task":"text-generation"}
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generation_config.json
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||||
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|
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|
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
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|
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|
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|
||||
"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\\n' + '```json' + '\\n' + tool['function']['arguments'] + '\\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\\n'}}{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<｜end▁of▁sentence｜>",
|
||||
"extra_special_tokens": {},
|
||||
"legacy": true,
|
||||
"model_max_length": 16384,
|
||||
"pad_token": "<｜end▁of▁sentence｜>",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizerFast",
|
||||
"unk_token": null,
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user