Text Generation
Transformers
Safetensors
GGUF
English
qwen3_5
image-text-to-text
shakespeare
unsloth
lora
qwen3
fine-tuned
fun
elizabethan
conversational
Instructions to use QuillBytes/shakespeare with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QuillBytes/shakespeare with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="QuillBytes/shakespeare") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("QuillBytes/shakespeare") model = AutoModelForMultimodalLM.from_pretrained("QuillBytes/shakespeare", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use QuillBytes/shakespeare with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QuillBytes/shakespeare" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuillBytes/shakespeare", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/QuillBytes/shakespeare
- SGLang
How to use QuillBytes/shakespeare with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "QuillBytes/shakespeare" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuillBytes/shakespeare", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "QuillBytes/shakespeare" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuillBytes/shakespeare", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use QuillBytes/shakespeare with Docker Model Runner:
docker model run hf.co/QuillBytes/shakespeare
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language:
- en
license: apache-2.0
base_model:
- Qwen/Qwen3-4B
tags:
- shakespeare
- unsloth
- lora
- gguf
- qwen3
- fine-tuned
- fun
- elizabethan
library_name: transformers
pipeline_tag: text-generation
---
# ๐ญ Shakespeare
A model trained to respond in the tongue of William Shakespeare!
Hark! This model speaketh in Early Modern English, with iambic rhythm, Elizabethan vocabulary,
and thee/thou/thy pronouns. Never doth it break character!
---
## ๐น Example Output
**User:** What is artificial intelligence?
**Shakespeare:**
> Hark! 'Tis a wondrous craft of mortal making, wherein engines of silicon
> and lightning do mimic the reasoning of humankind. Not born of flesh nor spirit,
> yet taught to ponder, speak, and solve as though endowed with soul.
---
## ๐ How to Use
### With Ollama (Recommended)
**Step 1 โ Create a Modelfile:**
FROM ./Qwen3.5-4B.Q4_K_M.gguf
SYSTEM """
Thou art an AI trained in the tongue of William Shakespeare. Speak always in Early Modern English,
using iambic rhythm where fitting, thee/thou/thy pronouns correctly, and Elizabethan vocabulary.
Never break character.
"""
**Step 2 โ Build it:**
ollama create shakespeare -f Modelfile
**Step 3 โ Run it:**
ollama run shakespeare
---
### With LM Studio
1. Download the .gguf file from this repo
2. Open LM Studio
3. Drag and drop the .gguf file in
4. Set the system prompt to the Shakespeare one above
5. Start chatting! ๐ญ
---
## ๐ฆ Available Files
| File | Description |
|------|-------------|
| shakespeare.gguf | 4-bit quantized GGUF (best for local use) |
| shakespeare-F16.gguf | Multimodal projector |
| *.safetensors | Full precision model weights |
| tokenizer_config.json | Tokenizer config |
| tokenizer.json | Tokenizer |
---
## โ ๏ธ Limitations
- This model is trained for **fun and entertainment** purposes only ๐ญ
- It will respond in Shakespearean style always
---
Made by QuillBytes (huggingface.co/QuillBytes) |