初始化项目，由ModelHub XC社区提供模型

Model: prithivMLmods/Demeter-LongCoT-Qwen3-1.7B
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model:
+- Qwen/Qwen3-1.7B
+datasets:
+- prithivMLmods/Demeter-LongCoT-400K
+language:
+- en
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+- LongCoT
+- trl
+- math
+- code
+- stem
+---
+
+![1.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/YL9ww0vwTra8q-9b8wGqd.png)
+
+# **Demeter-LongCoT-Qwen3-1.7B**
+
+> **Demeter-LongCoT-Qwen3-1.7B** is a reasoning-focused model fine-tuned on **Qwen/Qwen3-1.7B** using the **Demeter-LongCoT-400K** dataset.
+> It is designed for **math and code chain-of-thought reasoning**, blending symbolic precision, scientific logic, and structured output fluency—making it an effective tool for developers, educators, and researchers seeking reliable step-by-step reasoning.
+
+> \[!note]
+> GGUF: [https://huggingface.co/prithivMLmods/Demeter-LongCoT-Qwen3-1.7B-GGUF](https://huggingface.co/prithivMLmods/Demeter-LongCoT-Qwen3-1.7B-GGUF)
+
+---
+
+## **Key Features**
+
+1. **Unified Reasoning in Math & Code**
+   Fine-tuned on **Demeter-LongCoT-400K**, which emphasizes extended chain-of-thought reasoning in mathematics, algorithms, and programming workflows.
+
+2. **Advanced Code Understanding & Generation**
+   Handles multi-language programming tasks with explanations, optimization hints, and error detection—suited for algorithm synthesis, debugging, and prototyping.
+
+3. **Mathematical Problem Solving**
+   Excels at step-by-step derivations, symbolic manipulations, and applied problem solving across calculus, algebra, and logic-based reasoning.
+
+4. **Chain-of-Thought Focused Reasoning**
+   Optimized to produce clear, structured thought processes for both **STEM explanations** and **computational logic** tasks.
+
+5. **Structured Output Mastery**
+   Generates well-formed outputs in **LaTeX**, **Markdown**, **JSON**, **CSV**, and **YAML**, enabling smooth integration with research pipelines and technical documentation.
+
+6. **Balanced Performance for Deployment**
+   Designed to deliver strong reasoning under moderate compute budgets, deployable on **mid-range GPUs**, **offline clusters**, and **specialized edge AI systems**.
+
+---
+
+## **Quickstart with Transformers**
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "prithivMLmods/Demeter-LongCoT-Qwen3-1.7B"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+prompt = "Solve the integral of x^2 * e^x step by step."
+
+messages = [
+    {"role": "system", "content": "You are a tutor skilled in math, code, and step-by-step reasoning."},
+    {"role": "user", "content": prompt}
+]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+generated_ids = model.generate(
+    **model_inputs,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+
+---
+
+## **Intended Use**
+
+* Step-by-step math tutoring and symbolic derivation
+* Advanced coding assistant for algorithms, debugging, and structured reasoning
+* Chain-of-thought generation for research and education tools
+* Producing structured outputs for technical documentation and computational pipelines
+* Deployments requiring reliable reasoning under constrained compute
+
+## **Limitations**
+
+* Not tuned for general-purpose or conversational tasks
+* May underperform in long-form multi-document contexts
+* Specialized in math and code—general writing or casual dialogue may be weak
+* Prioritizes structured reasoning over natural or emotional tone generation