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---
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language: en
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license: openrail
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datasets:
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- custom_pilgrims_dataset
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tags:
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- wizardlm
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- lora
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- finetuned
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- conversational
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- assistant
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pipeline_tag: text-generation
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---
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# WizardLM Fine-Tuned on Pilgrims Dataset
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This model is a fine-tuned version of [TheBloke/wizardLM-7B-HF](https://huggingface.co/TheBloke/wizardLM-7B-HF) using QLoRA on a custom dataset designed around spiritual, philosophical, and existential questions.
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---
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## Model Description
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- **Base Model:** WizardLM 7B (HF format)
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- **Fine-tuning Method:** QLoRA (Quantized Low-Rank Adaptation)
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- **Training Data:** Custom pilgrims dataset (e.g. `Vibe: Atheist\nQuestion: How can I...`)
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- **Intended Use:** Conversational assistant for users exploring personal meaning, spiritual identity, or philosophical reflection.
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---
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## Usage Example
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("chaima01/wizard-pilgrims-finetuned")
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tokenizer = AutoTokenizer.from_pretrained("chaima01/wizard-pilgrims-finetuned")
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input_text = "#### Human: Vibe: Atheist\nQuestion: How can I really get to know who I am beyond all the labels and roles I’ve taken on?"
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inputs = tokenizer(input_text, return_tensors="pt").to(model.device)
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outputs = model.generate(
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inputs.input_ids,
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max_new_tokens=256,
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temperature=0.7,
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