"slow":始终使用慢速tokenizer。 安全性和远程代码信任参数 --trust-remote-code:信任来自Hugging Face的远程代码。 下载与加载路径参数 --download-dir <directory>:模型权重下载和加载的目录,默认为Hugging Face的缓存目录。 模型权重加载格式参数 --load-format {auto,pt,safetensors,npcache,dummy,tensorizer...
python3 -m vllm.entrypoints.openai.api_server\--model=/workspace/DeepSeek-R1\--dtype=auto\--block-size32\--tokenizer-mode=slow\--max-model-len32768\--max-num-batched-tokens2048\--tensor-parallel-size8\--pipeline-parallel-size3\--gpu-memory-utilization 0.90\--max-num-seqs128\--trust-...
model_type in _MODEL_TYPES_WITH_SLOW_TOKENIZER: if kwargs.get("use_fast", False) == True: raise ValueError( f"Cannot use the fast tokenizer for {config.model_type} due to " "bugs in the fast tokenizer.") logger.info( f"Using the slow tokenizer for {config.model_type} ...
38 + logger.warning( 39 + "Using a slow tokenizer. This might cause a significant " 40 + "slowdown. Consider using a fast tokenizer instead.") 41 + return tokenizer 44 42 45 43 46 44 def detokenize_incrementally( 0 commit comments Comments0 (0) Please sign in to comment....
vllm [用法]:当v0.5.0版本支持bitsandbytes时，我可以使用vlm.LLM(quantization="bitsandbytes"......
[Bug]: vllm部署GLM-4V时报告KeyError: 'transformer.vision.transformer.layers.45.mlp.fc2.weight'GLM...
字符类型参数 --model: 模型路径 --tokenizer: 分词器路径,可选参数,若没有设置,默认使用model路径下的 --tokenizer-mode: 有 auto 和 slow 可选,默认使用 auto --dtype: 可选项有 'auto', 'half', 'float16', 'bfloat16', 'float', 'float32',默认为 auto, 若启动命令没有设置,则以模型下面的 ...
This class includes a tokenizer, a language model (possibly distributed across multiple GPUs), and GPU memory space allocated for intermediate states (aka KV cache). Given a batch of prompts and sampling parameters, this class generates texts from the model, using an intelligent batching ...
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It can be a branch name, a tag name, or a commit id. If unspecified, will use the default version. .. option:: --tokenizer-mode {auto,slow} The tokenizer mode. * "auto" will use the fast tokenizer if available. * "slow" will always use the slow tokenizer. .. option:: --...