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--- |
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license: mit |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- shakespeare |
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- chatbot |
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- tinyllama |
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- fine-tuned |
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- conversational |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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pipeline_tag: text-generation |
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--- |
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# TinyLlama Shakespeare Chatbot |
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A conversational AI that speaks in authentic Shakespearean English. |
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## Model Description |
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Fine-tuned on Shakespeare's complete works (42,000+ lines) transformed into 8,000+ chat-style training examples. |
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**Capabilities:** |
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- Compose sonnets on any topic |
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- Engage in dramatic dialogue |
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- Respond in Shakespearean style |
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- Generate poetry and monologues |
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**This is a MERGED model** - works directly with transformers, no PEFT needed! |
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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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model = AutoModelForCausalLM.from_pretrained( |
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"Akash-nath29/tinyllamashakespeare", |
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torch_dtype=torch.float16, |
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device_map="auto" |
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) |
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tokenizer = AutoTokenizer.from_pretrained("Akash-nath29/tinyllamashakespeare") |
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# Generate text |
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inputs = tokenizer("To be or not to be", return_tensors="pt") |
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outputs = model.generate(**inputs, max_length=200) |
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print(tokenizer.decode(outputs[0])) |
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` |
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## Training Details |
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| Parameter | Value | |
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|-----------|-------| |
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| Base Model | TinyLlama-1.1B-Chat-v1.0 | |
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| Method | LoRA + QLoRA (4-bit) | |
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| LoRA Rank | 16 | |
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| LoRA Alpha | 32 | |
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| Target Modules | q_proj, k_proj, v_proj, o_proj | |
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| Training Examples | 8,000+ conversations | |
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| Max Length | 512 tokens | |
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| Epochs | 3 | |
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## Hardware |
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- GPU: NVIDIA GeForce RTX 3050 Laptop GPU |
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- Training Time: ~4 hours |
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## Developed By |
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[Akash Nath](https://github.com/Akash-nath29) |
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## Repository |
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[GitHub - TinyLlamaShakespeare](https://github.com/Akash-nath29/TinyLlamaShakespeare) |
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## License |
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MIT License
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