初始化项目，由ModelHub XC社区提供模型

Model: gustavecortal/Qwen3-psychological-reasoning-8B
Source: Original Platform

README.md

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+---
+license: mit
+datasets:
+- cognitivecomputations/dolphin-r1
+- GeneralReasoning/GeneralThought-430K
+- gustavecortal/PsychologicalReasoning-15k
+language:
+- en
+pipeline_tag: text-generation
+base_model:
+- Qwen/Qwen3-8B
+tags:
+- philosophy
+- psychology
+- reasoning
+- social
+- emotion
+---
+
+## Presentation
+
+Qwen3-psychological-reasoning, a language model finetuned on 15k psychological and philosophical reasoning traces.
+
+Qwen3-psychological-reasoning is based on Qwen3 and was finetuned on a subset of open reasoning traces from [Dolphin R1](https://huggingface.co/datasets/cognitivecomputations/dolphin-r1) and [General Reasoning](https://huggingface.co/datasets/GeneralReasoning/GeneralThought-430K).
+
+Available sizes are: [0.6B](https://huggingface.co/gustavecortal/Qwen3-psychological-reasoning-0.6B), [1.7B](https://huggingface.co/gustavecortal/Qwen3-psychological-reasoning-1.7B), [4B](https://huggingface.co/gustavecortal/Qwen3-psychological-reasoning-4B), [8B](https://huggingface.co/gustavecortal/Qwen3-psychological-reasoning-8B).
+
+## How to use
+
+ ```py
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers.pipelines import pipeline
+import torch
+
+repo = "gustavecortal/Qwen3-psychological-reasoning-8B"
+tokenizer = AutoTokenizer.from_pretrained(repo, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    repo, torch_dtype=torch.bfloat16, device_map="auto", trust_remote_code=True
+)
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+prompt = tokenizer.apply_chat_template(
+    [
+        {
+            "role": "user",
+            "content": "Create a new psychotherapeutic technique based on cybernetic principles",
+        }
+    ],
+    tokenize=False,
+    add_generation_prompt=True,
+    enable_thinking=True,
+)
+
+print(pipe(prompt, max_new_tokens=2048, do_sample=True)[0]["generated_text"])
+```
+
+## Methodology
+
+We perform domain filtering on [Dolphin R1](https://huggingface.co/datasets/cognitivecomputations/dolphin-r1) and [General Reasoning](https://huggingface.co/datasets/GeneralReasoning/GeneralThought-430K). 
+
+Prompts are embedded, clustered with k-means (k=20 000) and majority-voted for domain labels using [Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B), following the [Intelligent Internet pipeline](https://huggingface.co/Intelligent-Internet/II-Medical-8B-1706). 
+
+Clusters tagged psychology or philosophy were retained for LoRA finetuning (rank=8, alpha=16, max length=2048, epoch=1, batch size=16).
+
+This work was performed using HPC resources (Jean Zay supercomputer) from GENCI-IDRIS (Grant 20XX-AD011014205).
+
+## Inspiration
+
+Qwen3-psychological-reasoning aims to reason about psychological and philosophical concepts such as self-image, emotion, and existence.
+
+Qwen3-psychological-reasoning was inspired by my position paper on emotion analysis: [Improving Language Models for Emotion Analysis: Insights from Cognitive Science](https://aclanthology.org/2024.cmcl-1.23/).
+
+## Contact
+
+Mail: gustave.cortal@ens-paris-saclay.fr
+
+Website: [gustavecortal.com](gustavecortal.com)