初始化项目，由ModelHub XC社区提供模型

Model: khazarai/Averroes-R1
Source: Original Platform

README.md

@@ -0,0 +1,133 @@
+---
+library_name: transformers
+tags:
+- unsloth
+- philosophy
+- debate
+- sft
+license: apache-2.0
+datasets:
+- mattwesney/CoT_Philosophical_Understanding
+language:
+- en
+base_model:
+- unsloth/Qwen3-1.7B
+pipeline_tag: text-generation
+---
+
+# Model Card for Averroes-R1
+
+
+![20250406_1550_Purple Thought Chain_simple_compose_01jr6ae7f7fwcv2jkp99qpjr8z.png](https://cdn-uploads.huggingface.co/production/uploads/65dbedfd2f6d2dfc27763b98/sOvQj9PxajgTatFbUbV1b.png)
+
+
+## Model Details
+
+### Model Description
+
+- **Base Model:** Qwen3-1.7B
+- **Language(s) (NLP):** English
+- **License:** MIT
+- **Task:** Foundational Philosophical Reasoning with Chain-of-Thought (CoT)
+- **Model Type:** Instruction-tuned model emphasizing logical and conceptual reasoning in philosophy
+- **Dataset:** [moremilk/CoT_Philosophical_Understanding](https://huggingface.co/datasets/moremilk/CoT_Philosophical_Understanding)
+
+
+## Uses
+
+### Direct Use
+
+The model is designed for:
+
+- Educational use in teaching and learning philosophy
+- Supporting AI assistants and chatbots focused on structured reasoning and conceptual understanding
+- Serving as a tool for structured philosophical explanation
+- Enhancing automated reasoning systems in conceptual and abstract domains
+
+It is not intended to replace human philosophical analysis or provide moral/personal advice.
+
+## Out of Scope
+
+This model is not designed for:
+
+- In-depth exploration of specialized or niche philosophical debates
+- Providing personal philosophical advice or opinions
+- Real-time discussion or analysis of ongoing philosophical issues
+- Handling highly subjective or interpretive arguments lacking foundational grounding
+
+## Bias, Risks, and Limitations
+
+- May simplify nuanced philosophical perspectives
+- Not suitable for advanced research or subjective debate
+- Outputs depend on prompt clarity; ambiguous inputs may yield incomplete reasoning
+- Trained for foundational reasoning, not for exhaustive domain knowledge
+
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("khazarai/Averroes-R1")
+model = AutoModelForCausalLM.from_pretrained(
+    "khazarai/Averroes-R1",
+    device_map={"": 0}
+)
+
+question = """
+What is the existentialist dilemma of freedom, and how do concepts like responsibility, anguish, and bad faith relate to it, according to Sartre?
+"""
+
+messages = [
+    {"role" : "user", "content" : question}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize = False,
+    add_generation_prompt = True,
+    enable_thinking = True,
+)
+
+from transformers import TextStreamer
+_ = model.generate(
+    **tokenizer(text, return_tensors = "pt").to("cuda"),
+    max_new_tokens = 2200,
+    temperature = 0.6,
+    top_p = 0.95,
+    top_k = 20,
+    streamer = TextStreamer(tokenizer, skip_prompt = True),
+)
+```
+
+
+## Training Data
+
+**Scope**
+
+This model was fine-tuned on tasks emphasizing foundational philosophical reasoning, focusing on:
+
+- Understanding key philosophical concepts across major branches (ethics, epistemology, metaphysics, logic, etc.)
+
+- Explaining philosophical principles through clear examples and structured reasoning
+
+- Highlighting the logical and conceptual steps behind philosophical inquiry
+
+- Building a strong foundational understanding of philosophical thought
+
+**Illustrative Examples**
+
+- Explaining the difference between empiricism and rationalism
+
+- Describing the reasoning behind the categorical imperative
+
+- Analyzing simple logical fallacies within philosophical arguments
+
+**Emphasis on Chain-of-Thought (CoT)**
+
+The dataset explicitly teaches step-by-step reasoning, allowing the model to show intermediate thoughts when analyzing or explaining philosophical ideas.
+
+**Focus on Foundational Knowledge**
+
+Rather than diving into complex, specialized debates, the dataset helps build a broad, structured foundation for philosophical reasoning.