DEPRECATED MODEL NOTICE
Please note that this model is no longer maintained or supported by our team. We strongly advise against using it in production or for any critical applications.
Instead, we recommend using our latest and greatest models, which can be found at:
https://huggingface.co/collections/Writer/palmyra-writer-license-66476fa8156169f8720a2c89
Palmyra Large 20B
Palmyra-Large is a 20B parameters causal decoder-only model built by Writer and trained on +800B tokens of Palmyra-Index-Data enhanced with curated corpora.
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Model Details
Palmyra Large was primarily pre-trained with English text. Note that there is still a trace amount of non-English data present within the training corpus that was accessed through CommonCrawl. A causal language modeling (CLM) objective was utilized during the process of the model's pretraining. Similar to GPT-3, Palmyra Large is a member of the same family of models that only contain a decoder. As a result, it was pre-trained utilizing the objective of self-supervised causal language modeling.
Model Description
- Developed by: https://www.writer.com;
- Model type: Causal decoder-only;
- Language(s) (NLP): English (and limited capabilities in German, Spanish, French, Swedish);
- License: Apache 2.0 license.
Uses
Direct Use
Research on large language models; as a foundation for further specialization and finetuning for specific usecases (e.g., summarization, text generation, chatbot, etc.)
Out-of-Scope Use
Production use without adequate assessment of risks and mitigation; any use cases which may be considered irresponsible or harmful.
Bias, Risks, and Limitations
Palmyra-large-20B is trained mostly on English with limited capabilities also in German, Spanish, French, Swedish. It will not generalize appropriately to other languages. Furthermore, as it is trained on a large-scale corpora representative of the web, it will carry the stereotypes and biases commonly encountered online.
Recommendations
We recommend users of Palmyra-Large-20B to consider finetuning it for the specific set of tasks of interest, and for guardrails and appropriate precautions to be taken for any production use.
Use case
Palmyra Large is extremely powerful while being extremely fast. This model excels at many nuanced tasks such as sentiment classification and summarization.
Training data
Palmyra Large (20b) was trained on Writer’s custom dataset.
Intended Use and Limitations
Palmyra Large learns an inner representation of the English language that can be used to extract features useful for downstream tasks. However, the model is best at what it was pre-trained for which is generating text from a prompt.
How to use
This model can be easily loaded using the AutoModelForCausalLM functionality:
import os
from transformers import AutoModelForCausalLM, AutoTokenizer
# set HF environment variable
auth_token = os.environ.get("HF_TOKEN", True)
model = AutoModelForCausalLM.from_pretrained(
"Writer/palmyra-large",
device_map="auto",
torch_dtype=torch.float16,
use_auth_token=auth_token,
)
tokenizer = AutoTokenizer.from_pretrained(
"Writer/palmyra-large", use_auth_token=auth_token
)
It can also be used with text-generation-inference
model=Writer/palmyra-large
volume=$PWD/data
docker run --gpus all --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference --model-id $model
Limitations and Biases
Palmyra Large’s core functionality is to take a string of text and predict the next token. While language models are widely used for other tasks, there are many unknowns in this work. When prompting Palmyra Large, keep in mind that the next statistically likely token is not always the token that produces the most "accurate" text. Never rely on Palmyra Large to produce factually correct results.
Palmyra Large was trained on Writer’s custom data. As with all language models, it is difficult to predict how Palmyra Large will respond to specific prompts, and offensive content may appear unexpectedly. We recommend that the outputs be curated or filtered by humans before they are released, both to censor undesirable content and to improve the quality of the results.
Citation and Related Information
To cite this model:
@misc{Palmyra,
author = {Writer Engineering team},
title = {{Palmyra-Large Parameter Autoregressive Language Model}},
howpublished = {\url{https://dev.writer.com}},
year = 2023,
month = March
}