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

.gitattributes

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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)

added_tokens.json

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+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
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+  "<|fim_suffix|>": 151661,
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+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 12288,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 40960,
+  "max_window_layers": 36,
+  "model_type": "qwen3",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.53.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

configuration.json

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generation_config.json

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+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "4.53.0"
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special_tokens_map.json

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