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README.md

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+---
+license: apache-2.0
+base_model: teknium/OpenHermes-2.5-Mistral-7B
+tags:
+- generated_from_trainer
+- audiobook
+- fine-tuned
+- text-generation
+- lora
+- axolotl
+language:
+- en
+pipeline_tag: text-generation
+widget:
+- text: "Who is the main character in the story?"
+- text: "Describe the setting of the book."
+- text: "What are the main themes explored?"
+---
+
+# the-silver-pigs-finetuned
+
+This model was fine-tuned on audiobook content using the AudioBook Visualizer application.
+
+## Model Details
+
+- **Base Model**: teknium/OpenHermes-2.5-Mistral-7B
+- **Fine-tuning Method**: QLoRA (4-bit quantization with LoRA adapters)
+- **Training Framework**: Axolotl
+- **Training Infrastructure**: RunPod Serverless
+- **Upload Date**: 2025-08-11T03:57:51.529Z
+
+## Training Configuration
+
+- **LoRA Rank**: 32
+- **LoRA Alpha**: 16
+- **LoRA Dropout**: 0.05
+- **Target Modules**: q_proj, v_proj, k_proj, o_proj
+- **Learning Rate**: 2e-4
+- **Batch Size**: 2
+- **Gradient Accumulation**: 4
+- **Training Duration**: ~3 minutes
+
+## Usage with vLLM
+
+Deploy on RunPod serverless with these environment variables:
+
+```json
+{
+  "MODEL_NAME": "the-silver-pigs-finetuned",
+  "TRUST_REMOTE_CODE": "true",
+  "MAX_MODEL_LEN": "2048",
+  "DTYPE": "float16",
+  "ENABLE_LORA": "true"
+}
+```
+
+## Usage with Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base_model = "teknium/OpenHermes-2.5-Mistral-7B"
+model = AutoModelForCausalLM.from_pretrained(
+    base_model,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+model = PeftModel.from_pretrained(model, "the-silver-pigs-finetuned")
+
+tokenizer = AutoTokenizer.from_pretrained("the-silver-pigs-finetuned")
+
+# Query the model
+prompt = "Tell me about the main character."
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=200, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+## Training Data
+
+This model was fine-tuned on audiobook transcript data, processed into ~490 question-answer pairs covering:
+- Character descriptions and relationships
+- Plot events and summaries
+- Dialogue and memorable quotes
+- Settings and world-building details
+
+## Limitations
+
+- Model knowledge is limited to the specific audiobook content
+- May generate plausible but incorrect details
+- Performance on general tasks may differ from base model
+
+## Created With
+
+[AudioBook Visualizer](https://github.com/yourusername/audiobook-visualizer) - An application for fine-tuning LLMs on audiobook content.
+
+---
+*Original model path: /workspace/outputs*