初始化项目，由ModelHub XC社区提供模型

Model: alibidaran/Platio_merged_model Source: Original Platform
2026-06-18 00:35:19 +08:00
commit b0da249792
12 changed files with 2715 additions and 0 deletions
--- a/README.md
+++ b/README.md
@@ -0,0 +1,129 @@
+---
+license: mit
+datasets:
+- isaiahbjork/cot-logic-reasoning
+base_model:
+- meta-llama/Llama-3.1-8B-Instruct
+pipeline_tag: text-generation
+language:
+- en
+library_name: transformers
+---
+
+# PlaiTO 🧠✨  
+*A Reasoning-Focused Language Model for the Humanities*
+
+## Overview
+**PlaiTO** is a reasoning-oriented language model designed specifically for **humanities and social sciences**. Built on top of **LLaMA 3.1 8B**, PlaiTO emphasizes structured thinking, conceptual understanding, and analytical reasoning rather than surface-level text generation.
+
+The model performs especially well in domains where **theory, interpretation, decision-making, and human behavior** matter most.
+
+## Base Model
+- **Architecture:** LLaMA 3.1  
+- **Parameters:** 8B  
+- **Training Focus:** Reasoning, conceptual analysis, and humanities-oriented problem solving  
+
+## Target Domains
+PlaiTO is optimized for:
+- **Psychology**
+- **Management & Organizational Studies**
+- **Sociology**
+- Related humanities and social science disciplines
+
+Typical use cases include:
+- Theoretical analysis  
+- Case study reasoning  
+- Concept explanation and comparison  
+- Decision-making support  
+- Academic discussion and synthesis  
+
+## Benchmark Performance
+PlaiTO was evaluated on the **MMLU benchmark** using **100 samples** per subject area. Results show strong and consistent performance across key humanities domains:
+
+| Domain                   | Accuracy |
+|--------------------------|----------|
+| Professional Psychology  | **76%**  |
+| Management               | **74%**  |
+| Sociology                | **75%**  |
+
+These results indicate reliable reasoning capabilities in complex, abstract, and theory-heavy tasks.
+
+## Strengths
+- Strong **reasoning and analytical depth**
+- Better handling of **abstract concepts** and **human-centered problems**
+- Suitable for **academic**, **educational**, and **research-oriented** applications
+- Balanced performance across multiple humanities disciplines
+
+## Limitations
+- Not optimized for mathematics-heavy or symbolic reasoning tasks  
+- May underperform in domains requiring exact numerical computation  
+- As with all LLMs, outputs should be reviewed for accuracy in high-stakes settings  
+
+## Intended Use
+PlaiTO is intended for:
+- Research and academic exploration  
+- Educational tools and tutoring systems  
+- Decision-support in management and organizational contexts  
+- Exploratory analysis in psychology and sociology
+
+ #### Direct Usage 
+
+ ```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+from peft import PeftModel
+import torch
+
+# Define the model IDs
+base_model_name_or_path = "alibidaran/Platio_merged_model" # The base Llama-3-8B-Instruct model
+
+# 1. Configure 4-bit quantization
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.float16
+)
+
+# 2. Load the Base Model with the config
+# Use device_map="auto" for efficient loading with quantization
+# Use torch_dtype=torch.bfloat16 for Llama models with bnb
+model = AutoModelForCausalLM.from_pretrained(
+    base_model_name_or_path,# The PEFT adapter ID
+    quantization_config=bnb_config,
+    torch_dtype=torch.bfloat16,
+    device_map="cuda",
+)
+
+tokenizer=AutoTokenizer.from_pretrained(base_model_name_or_path)
+system_prompt="""
+    You are a reasonable expert who thinks and answer the users question.
+    Before respond first think and create a chain of thoughts in your mind.
+    Then respond to the client.
+    Your chain of thought and reflection must be in <thinking>..</thinking> format and your respond
+    should be in the <output>..</output> format.
+    """
+   
+    messages = [
+                {'role':'system','content':system_prompt},
+                {"role": "user", "content":message},
+
+                ] 
+      
+    inputs = tokenizer.apply_chat_template(
+            messages,
+        tokenize = True,
+        add_generation_prompt = True, # Must add for generation
+        return_tensors = "pt",).to("cuda")
+    inputs_shape=inputs['input_ids'].shape[1]
+    with torch.no_grad():
+        output=model.generate(**inputs, max_new_tokens =2048,
+                   use_cache = True, temperature = 0.5, min_p = 0.9)
+
+
+````
+
+## Ethical Considerations
+While PlaiTO is designed to reason about human behavior and society, it should **not** be used as a replacement for professional judgment in clinical, legal, or organizational decision-making. Always apply human oversight.
+
+## License
+Please refer to the license of the base **LLaMA 3.1** model and ensure compliance with its terms.