if args.use_vllm: generation_config = dict( temperature=0.2, top_k=40, top_p=0.9, max_tokens=400, presence_penalty=1.0, ) else: generation_config = GenerationConfig( temperature=0.2, top_k=40, top_p=0.9, do_sample=True, num_beams=1, repetition_penalty=1.1, max_new_tokens=400 ) ...
from lmdeploy.model import ChatTemplateConfig backend_config = TurbomindEngineConfig(tp=2) chat_template_config = ChatTemplateConfig(model_name='llama3') gen_config = GenerationConfig(max_new_tokens=1024) pipe = lmdeploy.pipeline("/home/zhanghui/models/ChineseAlpacaGroup/llama-3-chinese-8b-instr...
评测集:SuperCLUE-Math6中文数学多步推理评测集,2024道多步推理数学题;SuperCLUE-Code3中文代码题,195道包含1560个测试用例。 模型GenerationConfig配置: 可参考Llama3官方文档: 测评方法: 1. SC-Math6是GSM8K的中文升级版,专门设计来评估和提升中文大模型在数学推理方面的核心能力。不仅延续了GSM8K的高质量和多样...
config): super().__init__(config) self.model = LlamaModel(config) self.vocab_size = config.vocab_size self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False) # Initialize weights and apply final processing self
│ ├── tokenizer_config.json │ ├── tokenizer.model │ └──USE_POLICY.md └── Llama-2-7b-chat-hf ├── added_tokens.json ├── config.json ├── generation_config.json ├──LICENSE.txt ├── model-00001-of-00002.safetensors ...
Llama-3.2-3B / generation_config.json generation_config.json 185 Bytes 一键复制 编辑 原始数据 按行查看 历史 Sanyam Bhutani 提交于 5个月前 . Adds missing delimiter in json file (#11) 123456789 { "_from_model_config": true, "bos_token_id": 128000, "eos_token_id": 128001, "...
[12621474981/12621474981] llama2-7b/ llama2-7b/generation_config.json llama2-7b/gitattributes.txt llama2-7b/config.json llama2-7b/pytorch_model.bin.index.json llama2-7b/USE_POLICY.md llama2-7b/README.md llama2-7b/LICENSE.txt llama2-7b/pytorch_model-00003-of-00003.bin llama2-7b/special...
# du -hs weights/*4.0K weights/config.json4.0K weights/generation_config.json9.3G weights/pytorch_model-00001-of-00002.bin3.3G weights/pytorch_model-00002-of-00002.bin 28K weights/pytorch_model.bin.index.json4.0K weights/special_tokens_map.json ...
具体来看实操演示~部署Llama 3微调训练推理 潞晨云提供一键部署功能，只需简单操作即可快速启动计算环境。在最开始时需要先创建云主机。比如对Llama3微调训练，可在8卡H800上完成，在算力市场中选择即可。此处选择Colossal-llama3训练微调镜像，单击创建按钮，创建云主机。确认当前路径名，并修改config文件，输入教程中的...
pad_token = self.tokenizer.eos_token # 初始化RAG组件 self.rag_tokenizer = RagTokenizer.from_pretrained(rag_name_or_path) self.rag_retriever = RagRetriever.from_pretrained(rag_name_or_path) self.rag_generator = RagSequenceForGeneration.from_pretrained(rag_name_or_path) print("...