Update README.md
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README.md
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@@ -11,7 +11,7 @@ license: llama2
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</div>
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<p align="center">
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π <a href="https://arxiv.org/abs/2402.12052" target="_blank">Paper</a> β’ π€ <a href="https://huggingface.co/zstanjj/SlimPLM-
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</p>
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<div align="center">
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@@ -38,10 +38,10 @@ params_query_rewrite = {"repetition_penalty": 1.05, "temperature": 0.01, "top_k"
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"max_new_tokens": 512, "do_sample": False, "seed": 2023}
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# deploy model
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model = AutoModelForCausalLM.from_pretrained("zstanjj/SlimPLM-
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if torch.cuda.is_available():
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model.cuda()
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tokenizer = AutoTokenizer.from_pretrained("zstanjj/SlimPLM-
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# run inference
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input_ids = tokenizer.encode(question, return_tensors="pt")
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</div>
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<p align="center">
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π <a href="https://arxiv.org/abs/2402.12052" target="_blank">Paper</a> β’ π€ <a href="https://huggingface.co/zstanjj/SlimPLM-Retrieval-Necessity-Judgment/" target="_blank">Hugging Face</a> ⒠𧩠<a href="https://github.com/plageon/SlimPLM" target="_blank">Github</a>
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</p>
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<div align="center">
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"max_new_tokens": 512, "do_sample": False, "seed": 2023}
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# deploy model
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model = AutoModelForCausalLM.from_pretrained("zstanjj/SlimPLM-Retrieval-Necessity-Judgment").eval()
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if torch.cuda.is_available():
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model.cuda()
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tokenizer = AutoTokenizer.from_pretrained("zstanjj/SlimPLM-Retrieval-Necessity-Judgment")
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# run inference
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input_ids = tokenizer.encode(question, return_tensors="pt")
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