update

inference.py

@@ -0,0 +1,49 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+"""
+单轮对话，不具有对话历史的记忆功能
+"""
+
+
+def main():
+    model_name = 'golaxy/gogpt2-7b'
+
+    max_new_tokens = 1024
+    top_p = 0.9
+    temperature = 0.95
+    repetition_penalty = 1.0
+    device = 'cuda'
+    input_pattern = '<s>{}</s>'
+    model = AutoModelForCausalLM.from_pretrained(
+        model_name,
+        trust_remote_code=True,
+        low_cpu_mem_usage=True,
+        torch_dtype=torch.float16,
+        device_map='auto'
+    ).to(device).eval()
+    tokenizer = AutoTokenizer.from_pretrained(
+        model_name,
+        trust_remote_code=True,
+        # llama不支持fast
+        use_fast=False if model.config.model_type == 'llama' else True
+    )
+    text = input('User：')
+    while True:
+        text = text.strip()
+        text = input_pattern.format(text)
+        input_ids = tokenizer(text, return_tensors="pt", add_special_tokens=False).input_ids.to(device)
+        with torch.no_grad():
+            outputs = model.generate(
+                input_ids=input_ids, max_new_tokens=max_new_tokens, do_sample=True,
+                top_p=top_p, temperature=temperature, repetition_penalty=repetition_penalty,
+                eos_token_id=tokenizer.eos_token_id
+            )
+        outputs = outputs.tolist()[0][len(input_ids[0]):]
+        response = tokenizer.decode(outputs)
+        response = response.strip().replace(text, "").replace('</s>', "").replace('<s>', "").strip()
+        print("Firefly：{}".format(response))
+        text = input('User：')
+
+
+if __name__ == '__main__':
+    main()