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Model: KNipun/whisper-psychology-gemma-3-1b Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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datasets:
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- jkhedri/psychology-dataset
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language:
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- en
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base_model:
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- google/gemma-3-1b-it
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- psychology,
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- mental-health,
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- chatbot,
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- fine-tuned,
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- gemma,
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- lora,
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---
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# Whisper Psychology Chatbot
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## Model Description
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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.
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**Developed by:** DeepFinders - SLTC Research University
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## Training Details
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- **Base Model:** google/gemma-3-1b-it
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- **Fine-tuning Method:** LoRA (Low-Rank Adaptation)
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- **Dataset:** jkhedri/psychology-dataset
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- **Training Samples:** ~2000 psychology conversations
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- **LoRA Configuration:**
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- r=8, lora_alpha=16
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- Target modules: q_proj, k_proj, v_proj, o_proj
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- Dropout: 0.1
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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# Load model and tokenizer
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model_name = "KNipun/whisper-psychology-gemma-3-1b"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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device_map="auto",
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torch_dtype=torch.float16
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)
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# Format conversation
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def chat_with_whisper(user_message):
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prompt = f"<start_of_turn>user\\n{user_message}<end_of_turn>\\n<start_of_turn>model\\n"
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inputs = tokenizer(prompt, return_tensors="pt")
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=150,
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temperature=0.7,
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do_sample=True,
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pad_token_id=tokenizer.eos_token_id
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)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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return response[len(prompt):]
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# Example usage
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response = chat_with_whisper("I'm feeling anxious about my upcoming exam. Can you help me?")
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print(response)
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```
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## Model Identity
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The model introduces itself as: "I'm Whisper, your mental health chatbot, developed by DeepFinders — an innovative student team at SLTC Research University."
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## Limitations
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- This model is for educational and research purposes
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- Not a replacement for professional mental health care
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- May generate incorrect or inappropriate responses
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- Should be used with appropriate safeguards and human oversight
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## Training Infrastructure
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- **Hardware:** Google Colab (GPU)
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- **Quantization:** 4-bit quantization during training
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- **Memory Optimization:** Gradient checkpointing, mixed precision (FP16)
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## Citation
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```bibtex
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@misc{whisper-psychology-2024,
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title={Whisper Psychology Chatbot},
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author={DeepFinders Team, SLTC Research University},
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year={2024},
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publisher={Hugging Face},
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url={https://huggingface.co/your-username/whisper-psychology-gemma-3-1b}
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}
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```
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## Ethical Considerations
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This model should be used responsibly with appropriate disclaimers about its limitations in providing mental health support.
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added_tokens.json
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added_tokens.json
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{
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"<image_soft_token>": 262144
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}
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chat_template.jinja
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chat_template.jinja
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{{ bos_token }}
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{%- if messages[0]['role'] == 'system' -%}
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{%- if messages[0]['content'] is string -%}
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{%- set first_user_prefix = messages[0]['content'] + '
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' -%}
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{%- else -%}
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{%- set first_user_prefix = messages[0]['content'][0]['text'] + '
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' -%}
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{%- endif -%}
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{%- set loop_messages = messages[1:] -%}
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{%- else -%}
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{%- set first_user_prefix = "" -%}
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{%- set loop_messages = messages -%}
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{%- endif -%}
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{%- for message in loop_messages -%}
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{%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
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{{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
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{%- endif -%}
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{%- if (message['role'] == 'assistant') -%}
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{%- set role = "model" -%}
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{%- else -%}
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{%- set role = message['role'] -%}
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{%- endif -%}
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{{ '<start_of_turn>' + role + '
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' + (first_user_prefix if loop.first else "") }}
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{%- if message['content'] is string -%}
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{{ message['content'] | trim }}
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{%- elif message['content'] is iterable -%}
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{%- for item in message['content'] -%}
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{%- if item['type'] == 'image' -%}
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{{ '<start_of_image>' }}
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{%- elif item['type'] == 'text' -%}
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{{ item['text'] | trim }}
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{%- endif -%}
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{%- endfor -%}
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{%- else -%}
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{{ raise_exception("Invalid content type") }}
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{%- endif -%}
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{{ '<end_of_turn>
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' }}
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{%- endfor -%}
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{%- if add_generation_prompt -%}
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{{'<start_of_turn>model
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'}}
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{%- endif -%}
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config.json
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config.json
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{
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"_sliding_window_pattern": 6,
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"architectures": [
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"Gemma3ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"attn_logit_softcapping": null,
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"eos_token_id": [
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],
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"final_logit_softcapping": null,
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"head_dim": 256,
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"hidden_activation": "gelu_pytorch_tanh",
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"hidden_size": 1152,
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"initializer_range": 0.02,
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"intermediate_size": 6912,
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"layer_types": [
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"sliding_attention",
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"full_attention",
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"sliding_attention",
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"sliding_attention"
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],
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"max_position_embeddings": 32768,
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"model_type": "gemma3_text",
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"num_attention_heads": 4,
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"num_hidden_layers": 26,
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"num_key_value_heads": 1,
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"pad_token_id": 0,
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"query_pre_attn_scalar": 256,
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"rms_norm_eps": 1e-06,
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"rope_local_base_freq": 10000,
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"rope_scaling": null,
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"rope_theta": 1000000,
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"sliding_window": 512,
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"torch_dtype": "float16",
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"transformers_version": "4.53.2",
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"use_cache": true,
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"vocab_size": 262144
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}
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generation_config.json
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generation_config.json
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{
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"do_sample": true,
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"eos_token_id": [
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"pad_token_id": 0,
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"top_k": 64,
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"top_p": 0.95,
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"transformers_version": "4.53.2"
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}
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model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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special_tokens_map.json
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{
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"boi_token": "<start_of_image>",
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"bos_token": {
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"lstrip": false,
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"lstrip": false,
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"normalized": false,
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"single_word": false
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"image_token": "<image_soft_token>",
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"pad_token": "<eos>",
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:bf1609194e85abbeb356094485d37d018739ec0ee6b79202044d43daf5ea982e
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size 33384833
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tokenizer.model
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tokenizer.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
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size 4689074
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tokenizer_config.json
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tokenizer_config.json
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