初始化项目，由ModelHub XC社区提供模型

Model: iamrahulreddy/Quintus Source: Original Platform
2026-06-28 21:11:02 +08:00
commit 930b4e9f2c
53 changed files with 9557 additions and 0 deletions
--- a/sft/chat.py
+++ b/sft/chat.py
@@ -0,0 +1,89 @@
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+import sys
+import argparse
+
+def main():
+    parser = argparse.ArgumentParser(description="Quintus Interactive Chat")
+    parser.add_argument("--model_path", type=str, default="iamrahulreddy/Quintus", help="Model repo ID or local weights directory")
+    parser.add_argument("--trust_remote_code", action="store_true", help="Allow custom code from the model repository.")
+    args = parser.parse_args()
+
+    model_path = args.model_path
+    print(f"Loading Quintus from {model_path}...")
+    try:
+        tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=args.trust_remote_code)
+        model = AutoModelForCausalLM.from_pretrained(
+            model_path,
+            device_map="auto",
+            dtype=torch.float16,
+            trust_remote_code=args.trust_remote_code
+        )
+    except Exception as e:
+        print(f"Error loading model: {e}")
+        print(f"Ensure '{model_path}' exists and contains the model weights.")
+        sys.exit(1)
+
+    # Defining stopping criteria
+    stop_tokens = ["<|endoftext|>", "<|im_end|>"]
+    eos_token_ids = [tokenizer.eos_token_id] if tokenizer.eos_token_id is not None else []
+    for token in stop_tokens:
+        t_id = tokenizer.convert_tokens_to_ids(token)
+        if t_id is not None and t_id not in eos_token_ids:
+            eos_token_ids.append(t_id)
+
+    streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+    conversation_history = [
+        {"role": "system", "content": "You are Quintus, a highly capable AI assistant created by Muskula Rahul. You are helpful, precise, and logically sound."}
+    ]
+
+    print()
+    print("Quintus Chat (type 'quit' to exit)")
+    print()
+
+    while True:
+        try:
+            user_input = input("You: ").strip()
+            if user_input.lower() in ["quit", "exit"]:
+                print("\nGoodbye!")
+                break
+            if not user_input:
+                continue
+
+            conversation_history.append({"role": "user", "content": user_input})
+
+            prompt = tokenizer.apply_chat_template(
+                conversation_history,
+                tokenize=False,
+                add_generation_prompt=True
+            )
+
+            inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+
+            print("Quintus: ", end="", flush=True)
+
+            with torch.no_grad():
+                outputs = model.generate(
+                    **inputs,
+                    max_new_tokens=512,
+                    temperature=0.7,
+                    top_p=0.9,
+                    do_sample=True,
+                    streamer=streamer,
+                    pad_token_id=tokenizer.eos_token_id,
+                    eos_token_id=eos_token_ids
+                )
+
+            # Extract response for history
+            generated_ids = outputs[0][inputs.input_ids.shape[-1]:]
+            assistant_response = tokenizer.decode(generated_ids, skip_special_tokens=True).strip()
+            conversation_history.append({"role": "assistant", "content": assistant_response})
+            print()
+
+        except KeyboardInterrupt:
+            print("\n\nGoodbye!")
+            break
+
+if __name__ == "__main__":
+    main()