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Capricornus-MoT-1.7B-Supreme1 is a high-precision, multi-domain expert model fine-tuned from Qwen3-1.7B, built for code generation, mathematical reasoning, scientific analysis, and open technical inference. Trained on the Mixture of Thoughts (MoT) dataset with combined expert clusters in code, math, and science, and enhanced with an Open Code Reasoning dataset, it delivers powerful symbolic and structured outputs in a wide range of STEM and reasoning domains.
1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_name = "prithivMLmods/Capricornus-MoT-1.7B-Supreme1"
4
5model = AutoModelForCausalLM.from_pretrained(
6 model_name,
7 torch_dtype="auto",
8 device_map="auto"
9)
10tokenizer = AutoTokenizer.from_pretrained(model_name)
11
12prompt = "Explain the code and solve the equation: Write a Python function to solve 2x + 3 = 11, and explain each step."
13
14messages = [
15 {"role": "system", "content": "You are an expert in math, code, and science reasoning."},
16 {"role": "user", "content": prompt}
17]
18
19text = tokenizer.apply_chat_template(
20 messages,
21 tokenize=False,
22 add_generation_prompt=True
23)
24
25model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
26
27generated_ids = model.generate(
28 **model_inputs,
29 max_new_tokens=512
30)
31generated_ids = [
32 output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
33]
34
35response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
36print(response)