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Update README.md
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README.md
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base_model:
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- Writer/Palmyra-X-004
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---
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- en
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base_model:
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- Writer/Palmyra-X-004
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---
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<div align="center">
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<h1>Palmyra-4-Creative, a powerful LLM designed for creative writing</h1>
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</div>
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### Model Description
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- **Developed by:** Writer
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- **Language(s) (NLP):** English
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- **License:** [Writer open model](https://writer.com/legal/acceptable-use/)
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- **Finetuned from model:** Palmyra-X-004
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- **Context window:** 131,072 tokens
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- **Parameters:** 122 billion
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## Model Details
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## Model Details
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Palmyra-4-Creative, developed by Writer, is a model designed to assist with creative writing and content generation tasks. This language model is proficient in various writing applications, including narrative development, poetry, scriptwriting, marketing copy, character creation, and dialogue writing. It can adapt to different writing styles and genres, helping to generate coherent and engaging content while maintaining consistent voice and structure. Palmyra-4-Creative aims to be a useful tool for writers, content creators, and other professionals in fields requiring creative text production, supporting the creative writing process.
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### Resources and Technical Documentation:
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#### Specialized for Creative Applications
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## Intended Use
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### Use with transformers
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You can run conversational inference using the Transformers Auto classes with the `generate()` function. Here's an example:
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```py
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "Writer/palmyra-4-creative"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto",
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attn_implementation="flash_attention_2",
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)
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messages = [
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{
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"role": "system",
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"content": "You are a highly creative and imaginative AI assistant, skilled in various forms of creative writing and ideation.",
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},
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{
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"role": "user",
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"content": "Write a short story opening that combines elements of science fiction and horror.",
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},
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]
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input_ids = tokenizer.apply_chat_template(
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messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
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)
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gen_conf = {
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"max_new_tokens": 256,
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"eos_token_id": [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids("<|eot_id|>")],
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"temperature": 0.7,
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"top_p": 0.9,
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}
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with torch.inference_mode():
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output_id = model.generate(input_ids, **gen_conf)
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output_text = tokenizer.decode(output_id[0][input_ids.shape[1] :])
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print(output_text)
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```
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### Evaluation Results
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### Citation and Related Information
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To cite this model:
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```
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@misc{Palmyra-4-Creative-70B,
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author = {Writer Engineering team},
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title = {{Palmyra-4-Creative: A powerful LLM designed for creative writing}},
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howpublished = {\url{https://dev.writer.com}},
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year = 2024,
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month = Oct
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}
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```
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Contact Hello@writer.com
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