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Model: KNipun/whisper-psychology-gemma-3-1b
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+datasets:
+- jkhedri/psychology-dataset
+language:
+- en
+base_model:
+- google/gemma-3-1b-it
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- psychology,
+- mental-health,
+- chatbot,
+- fine-tuned,
+- gemma,
+- lora,
+---
+
+# Whisper Psychology Chatbot
+
+## Model Description
+
+Whisper is a mental health chatbot fine-tuned on the Gemma-3-1B-IT model using psychology-focused conversational data. The model is designed to provide supportive and empathetic responses for mental health conversations.
+
+**Developed by:** DeepFinders - SLTC Research University
+
+## Training Details
+
+- **Base Model:** google/gemma-3-1b-it
+- **Fine-tuning Method:** LoRA (Low-Rank Adaptation)
+- **Dataset:** jkhedri/psychology-dataset
+- **Training Samples:** ~2000 psychology conversations
+- **LoRA Configuration:**
+  - r=8, lora_alpha=16
+  - Target modules: q_proj, k_proj, v_proj, o_proj
+  - Dropout: 0.1
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load model and tokenizer
+model_name = "KNipun/whisper-psychology-gemma-3-1b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    device_map="auto",
+    torch_dtype=torch.float16
+)
+
+# Format conversation
+def chat_with_whisper(user_message):
+    prompt = f"<start_of_turn>user\\n{user_message}<end_of_turn>\\n<start_of_turn>model\\n"
+    
+    inputs = tokenizer(prompt, return_tensors="pt")
+    
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=150,
+            temperature=0.7,
+            do_sample=True,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response[len(prompt):]
+
+# Example usage
+response = chat_with_whisper("I'm feeling anxious about my upcoming exam. Can you help me?")
+print(response)
+```
+
+## Model Identity
+
+The model introduces itself as: "I'm Whisper, your mental health chatbot, developed by DeepFinders — an innovative student team at SLTC Research University."
+
+## Limitations
+
+- This model is for educational and research purposes
+- Not a replacement for professional mental health care
+- May generate incorrect or inappropriate responses
+- Should be used with appropriate safeguards and human oversight
+
+## Training Infrastructure
+
+- **Hardware:** Google Colab (GPU)
+- **Quantization:** 4-bit quantization during training
+- **Memory Optimization:** Gradient checkpointing, mixed precision (FP16)
+
+## Citation
+
+```bibtex
+@misc{whisper-psychology-2024,
+  title={Whisper Psychology Chatbot},
+  author={DeepFinders Team, SLTC Research University},
+  year={2024},
+  publisher={Hugging Face},
+  url={https://huggingface.co/your-username/whisper-psychology-gemma-3-1b}
+}
+```
+
+## Ethical Considerations
+
+This model should be used responsibly with appropriate disclaimers about its limitations in providing mental health support.

added_tokens.json

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+{
+  "<image_soft_token>": 262144
+}

chat_template.jinja

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+{{ bos_token }}
+{%- if messages[0]['role'] == 'system' -%}
+    {%- if messages[0]['content'] is string -%}
+        {%- set first_user_prefix = messages[0]['content'] + '
+
+' -%}
+    {%- else -%}
+        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
+
+' -%}
+    {%- endif -%}
+    {%- set loop_messages = messages[1:] -%}
+{%- else -%}
+    {%- set first_user_prefix = "" -%}
+    {%- set loop_messages = messages -%}
+{%- endif -%}
+{%- for message in loop_messages -%}
+    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
+        {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
+    {%- endif -%}
+    {%- if (message['role'] == 'assistant') -%}
+        {%- set role = "model" -%}
+    {%- else -%}
+        {%- set role = message['role'] -%}
+    {%- endif -%}
+    {{ '<start_of_turn>' + role + '
+' + (first_user_prefix if loop.first else "") }}
+    {%- if message['content'] is string -%}
+        {{ message['content'] | trim }}
+    {%- elif message['content'] is iterable -%}
+        {%- for item in message['content'] -%}
+            {%- if item['type'] == 'image' -%}
+                {{ '<start_of_image>' }}
+            {%- elif item['type'] == 'text' -%}
+                {{ item['text'] | trim }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {{ raise_exception("Invalid content type") }}
+    {%- endif -%}
+    {{ '<end_of_turn>
+' }}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{'<start_of_turn>model
+'}}
+{%- endif -%}

config.json

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+{
+  "_sliding_window_pattern": 6,
+  "architectures": [
+    "Gemma3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": null,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": [
+    1,
+    106
+  ],
+  "final_logit_softcapping": null,
+  "head_dim": 256,
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 1152,
+  "initializer_range": 0.02,
+  "intermediate_size": 6912,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "model_type": "gemma3_text",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 26,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_local_base_freq": 10000,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": 512,
+  "torch_dtype": "float16",
+  "transformers_version": "4.53.2",
+  "use_cache": true,
+  "vocab_size": 262144
+}

generation_config.json

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+{
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "do_sample": true,
+  "eos_token_id": [
+    1,
+    106
+  ],
+  "pad_token_id": 0,
+  "top_k": 64,
+  "top_p": 0.95,
+  "transformers_version": "4.53.2"
+}

model.safetensors

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+size 1999810864

special_tokens_map.json

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+{
+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
+    "content": "<eos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "image_token": "<image_soft_token>",
+  "pad_token": "<eos>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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tokenizer.model

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