python -m vllm.entrypoints.openai.api_server --model Qwen/Qwen1.5-7B-Chat 然后，您可以使用 create chat interface 来与 Qwen 进行交流： curl http://localhost:8000/v1/chat/completions -H "Content-Type: application/json" --model Qwen/Qwen1.5-7B-Chat 你无需担心 chat 模板，因为它默认会使用由 tokenizer 提供的 chat 模板。 然后，您可以利用 create chat interface 来与 Qwen 进行对话： curl http://localhost:8000/v1/chat/completions -H "Content-Type: application/json"

think is better? Advantages (continued) • Which one do you think is better? PyTorch! • Easy Interface − easy to use API. The code execution in this framework is quite easy. Also need a fewer lines to

BERT-Small and BERT-Base variants. BERT_ENCODERS = { # Recommended, because it is fast and has same interface as base BERT 'bert-small': "https://tfhub.dev/tensorflow/small_bert/bert_en_uncased_L-2_H-128_A-2/2"

concatenate two inputs. It is defined below: keras.layers.concatenate(inputs, axis=-1) Functional interface to the Concatenate layer. Here, axis refers to Concatenation axis. dot It returns the dot

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