(self, num_gpu_blocks: int, num_cpu_blocks: int) -> None: """Allocate GPU and CPU KV cache with the specified number of blocks. This also warms up the model, which may record CUDA graphs. """ raise_if_cache_size_invalid(num_gpu_blocks, self.cache_config.block_size, self.model...
mask, pad_token_id=tokenizer.eostoken_id, temperature=0.6, max_new_tokens=8192, # 思考需要的 Token 数,设为 8K top_p=0.95) # 生成结果后处理:通过切片剔除输入部分,仅保留模型生成的内容 generated_ids = [ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input...
""" def __init__( self, device: Device, block_size: int, num_blocks: int, ) -> None: self.device = device # 设备:cpu/gpu self.block_size = block_size # 该设备上每个物理块的槽位数,默认为16 self.num_blocks = num_blocks # 该设备上留给KV cache的总物理块数量 # === # 初始化...
TORCH_CHECK(false, "Invalid device combination"); } void *src_ptr = src.data_ptr(); void *dst_ptr = dst.data_ptr(); char *src_ptr = static_cast<char*>(src.data_ptr()); char *dst_ptr = static_cast<char*>(dst.data_ptr()); const int64_t block_size_in_bytes = src.element...
[CUDA]: device kernel image is invalid Exception in callback functools.partial(<function _log_task_completion at 0x7ff67a845310>, error_callback=<bound method AsyncLLMEngine._error_callback of <vllm.engine.async_llm_engine.AsyncLLMEngine object at 0x7ff66058eac0>>) handle: <Handle ...
[Bug]: vLLM 在 AWS Inferentia (inf2) 上失败我认为这个错误主要是由于目前vLLM的神经元后端缺乏...
vllm --tensor-parallel-size 2 fails to load on GCP我在qwen72b模型上遇到了同样的问题。
流水线 model_id=“Trendyol/Trendyol-LM-7b-chat-v0.1” 词元分析器=LlamaTokenizer.from_pretrained(model_id) 模型=AutoModelForCausalLM.from_ pretrained(模型id, device_map=“自动”, load_in_8bit=真) sampling_params=dict(do_sample=True,温度=0.3,top_k=50,top_p=0.9) 管道=流水线(“文本...
第一步是合并到#7054。明天我会在主节点监控ci状态，看看pp测试和2个节点测试中是否还有失败。如果没有...
[Bug]: vLLM 在 AWS Inferentia (inf2) 上失败我认为这个错误主要是由于目前vLLM的神经元后端缺乏...