|
--- |
|
base_model: FPHam/Writing_Partner_Mistral_7B |
|
inference: false |
|
language: |
|
- en |
|
license: apache-2.0 |
|
model_creator: FPHam |
|
model_name: Writing Partner Mistral 7B |
|
model_type: mistral |
|
prompt_template: '<|im_start|>system |
|
|
|
{system_message}<|im_end|> |
|
|
|
<|im_start|>user |
|
|
|
{prompt}<|im_end|> |
|
|
|
<|im_start|>assistant |
|
|
|
' |
|
quantized_by: TheBloke |
|
tags: |
|
- mistral |
|
- instruct |
|
- finetune |
|
- chatml |
|
- gpt4 |
|
--- |
|
<!-- markdownlint-disable MD041 --> |
|
|
|
<!-- header start --> |
|
<!-- 200823 --> |
|
<div style="width: auto; margin-left: auto; margin-right: auto"> |
|
<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;"> |
|
</div> |
|
<div style="display: flex; justify-content: space-between; width: 100%;"> |
|
<div style="display: flex; flex-direction: column; align-items: flex-start;"> |
|
<p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/theblokeai">Chat & support: TheBloke's Discord server</a></p> |
|
</div> |
|
<div style="display: flex; flex-direction: column; align-items: flex-end;"> |
|
<p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p> |
|
</div> |
|
</div> |
|
<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">TheBloke's LLM work is generously supported by a grant from <a href="https://a16z.com">andreessen horowitz (a16z)</a></p></div> |
|
<hr style="margin-top: 1.0em; margin-bottom: 1.0em;"> |
|
<!-- header end --> |
|
|
|
# Writing Partner Mistral 7B - GPTQ |
|
- Model creator: [FPHam](https://huggingface.co/FPHam) |
|
- Original model: [Writing Partner Mistral 7B](https://huggingface.co/FPHam/Writing_Partner_Mistral_7B) |
|
|
|
<!-- description start --> |
|
# Description |
|
|
|
This repo contains GPTQ model files for [FPHam's Writing Partner Mistral 7B](https://huggingface.co/FPHam/Writing_Partner_Mistral_7B). |
|
|
|
Multiple GPTQ parameter permutations are provided; see Provided Files below for details of the options provided, their parameters, and the software used to create them. |
|
|
|
These files were quantised using hardware kindly provided by [Massed Compute](https://massedcompute.com/). |
|
|
|
<!-- description end --> |
|
<!-- repositories-available start --> |
|
## Repositories available |
|
|
|
* [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-AWQ) |
|
* [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ) |
|
* [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GGUF) |
|
* [FPHam's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/FPHam/Writing_Partner_Mistral_7B) |
|
<!-- repositories-available end --> |
|
|
|
<!-- prompt-template start --> |
|
## Prompt template: ChatML |
|
|
|
``` |
|
<|im_start|>system |
|
{system_message}<|im_end|> |
|
<|im_start|>user |
|
{prompt}<|im_end|> |
|
<|im_start|>assistant |
|
|
|
``` |
|
|
|
<!-- prompt-template end --> |
|
|
|
|
|
|
|
<!-- README_GPTQ.md-compatible clients start --> |
|
## Known compatible clients / servers |
|
|
|
These GPTQ models are known to work in the following inference servers/webuis. |
|
|
|
- [text-generation-webui](https://github.com/oobabooga/text-generation-webui) |
|
- [KoboldAI United](https://github.com/henk717/koboldai) |
|
- [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui) |
|
- [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference) |
|
|
|
This may not be a complete list; if you know of others, please let me know! |
|
<!-- README_GPTQ.md-compatible clients end --> |
|
|
|
<!-- README_GPTQ.md-provided-files start --> |
|
## Provided files, and GPTQ parameters |
|
|
|
Multiple quantisation parameters are provided, to allow you to choose the best one for your hardware and requirements. |
|
|
|
Each separate quant is in a different branch. See below for instructions on fetching from different branches. |
|
|
|
Most GPTQ files are made with AutoGPTQ. Mistral models are currently made with Transformers. |
|
|
|
<details> |
|
<summary>Explanation of GPTQ parameters</summary> |
|
|
|
- Bits: The bit size of the quantised model. |
|
- GS: GPTQ group size. Higher numbers use less VRAM, but have lower quantisation accuracy. "None" is the lowest possible value. |
|
- Act Order: True or False. Also known as `desc_act`. True results in better quantisation accuracy. Some GPTQ clients have had issues with models that use Act Order plus Group Size, but this is generally resolved now. |
|
- Damp %: A GPTQ parameter that affects how samples are processed for quantisation. 0.01 is default, but 0.1 results in slightly better accuracy. |
|
- GPTQ dataset: The calibration dataset used during quantisation. Using a dataset more appropriate to the model's training can improve quantisation accuracy. Note that the GPTQ calibration dataset is not the same as the dataset used to train the model - please refer to the original model repo for details of the training dataset(s). |
|
- Sequence Length: The length of the dataset sequences used for quantisation. Ideally this is the same as the model sequence length. For some very long sequence models (16+K), a lower sequence length may have to be used. Note that a lower sequence length does not limit the sequence length of the quantised model. It only impacts the quantisation accuracy on longer inference sequences. |
|
- ExLlama Compatibility: Whether this file can be loaded with ExLlama, which currently only supports Llama and Mistral models in 4-bit. |
|
|
|
</details> |
|
|
|
| Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc | |
|
| ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- | |
|
| [main](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ/tree/main) | 4 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-raw-v1) | 4096 | 4.16 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. | |
|
| [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-raw-v1) | 4096 | 4.57 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. | |
|
| [gptq-8bit--1g-actorder_True](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ/tree/gptq-8bit--1g-actorder_True) | 8 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-raw-v1) | 4096 | 7.52 GB | No | 8-bit, with Act Order. No group size, to lower VRAM requirements. | |
|
| [gptq-8bit-128g-actorder_True](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ/tree/gptq-8bit-128g-actorder_True) | 8 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-raw-v1) | 4096 | 7.68 GB | No | 8-bit, with group size 128g for higher inference quality and with Act Order for even higher accuracy. | |
|
| [gptq-8bit-32g-actorder_True](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ/tree/gptq-8bit-32g-actorder_True) | 8 | 32 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-raw-v1) | 4096 | 8.17 GB | No | 8-bit, with group size 32g and Act Order for maximum inference quality. | |
|
| [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-raw-v1) | 4096 | 4.30 GB | Yes | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. | |
|
|
|
<!-- README_GPTQ.md-provided-files end --> |
|
|
|
<!-- README_GPTQ.md-download-from-branches start --> |
|
## How to download, including from branches |
|
|
|
### In text-generation-webui |
|
|
|
To download from the `main` branch, enter `TheBloke/Writing_Partner_Mistral_7B-GPTQ` in the "Download model" box. |
|
|
|
To download from another branch, add `:branchname` to the end of the download name, eg `TheBloke/Writing_Partner_Mistral_7B-GPTQ:gptq-4bit-32g-actorder_True` |
|
|
|
### From the command line |
|
|
|
I recommend using the `huggingface-hub` Python library: |
|
|
|
```shell |
|
pip3 install huggingface-hub |
|
``` |
|
|
|
To download the `main` branch to a folder called `Writing_Partner_Mistral_7B-GPTQ`: |
|
|
|
```shell |
|
mkdir Writing_Partner_Mistral_7B-GPTQ |
|
huggingface-cli download TheBloke/Writing_Partner_Mistral_7B-GPTQ --local-dir Writing_Partner_Mistral_7B-GPTQ --local-dir-use-symlinks False |
|
``` |
|
|
|
To download from a different branch, add the `--revision` parameter: |
|
|
|
```shell |
|
mkdir Writing_Partner_Mistral_7B-GPTQ |
|
huggingface-cli download TheBloke/Writing_Partner_Mistral_7B-GPTQ --revision gptq-4bit-32g-actorder_True --local-dir Writing_Partner_Mistral_7B-GPTQ --local-dir-use-symlinks False |
|
``` |
|
|
|
<details> |
|
<summary>More advanced huggingface-cli download usage</summary> |
|
|
|
If you remove the `--local-dir-use-symlinks False` parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: `~/.cache/huggingface`), and symlinks will be added to the specified `--local-dir`, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model. |
|
|
|
The cache location can be changed with the `HF_HOME` environment variable, and/or the `--cache-dir` parameter to `huggingface-cli`. |
|
|
|
For more documentation on downloading with `huggingface-cli`, please see: [HF -> Hub Python Library -> Download files -> Download from the CLI](https://huggingface.co/docs/huggingface_hub/guides/download#download-from-the-cli). |
|
|
|
To accelerate downloads on fast connections (1Gbit/s or higher), install `hf_transfer`: |
|
|
|
```shell |
|
pip3 install hf_transfer |
|
``` |
|
|
|
And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`: |
|
|
|
```shell |
|
mkdir Writing_Partner_Mistral_7B-GPTQ |
|
HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/Writing_Partner_Mistral_7B-GPTQ --local-dir Writing_Partner_Mistral_7B-GPTQ --local-dir-use-symlinks False |
|
``` |
|
|
|
Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command. |
|
</details> |
|
|
|
### With `git` (**not** recommended) |
|
|
|
To clone a specific branch with `git`, use a command like this: |
|
|
|
```shell |
|
git clone --single-branch --branch gptq-4bit-32g-actorder_True https://huggingface.co/TheBloke/Writing_Partner_Mistral_7B-GPTQ |
|
``` |
|
|
|
Note that using Git with HF repos is strongly discouraged. It will be much slower than using `huggingface-hub`, and will use twice as much disk space as it has to store the model files twice (it stores every byte both in the intended target folder, and again in the `.git` folder as a blob.) |
|
|
|
<!-- README_GPTQ.md-download-from-branches end --> |
|
<!-- README_GPTQ.md-text-generation-webui start --> |
|
## How to easily download and use this model in [text-generation-webui](https://github.com/oobabooga/text-generation-webui) |
|
|
|
Please make sure you're using the latest version of [text-generation-webui](https://github.com/oobabooga/text-generation-webui). |
|
|
|
It is strongly recommended to use the text-generation-webui one-click-installers unless you're sure you know how to make a manual install. |
|
|
|
1. Click the **Model tab**. |
|
2. Under **Download custom model or LoRA**, enter `TheBloke/Writing_Partner_Mistral_7B-GPTQ`. |
|
|
|
- To download from a specific branch, enter for example `TheBloke/Writing_Partner_Mistral_7B-GPTQ:gptq-4bit-32g-actorder_True` |
|
- see Provided Files above for the list of branches for each option. |
|
|
|
3. Click **Download**. |
|
4. The model will start downloading. Once it's finished it will say "Done". |
|
5. In the top left, click the refresh icon next to **Model**. |
|
6. In the **Model** dropdown, choose the model you just downloaded: `Writing_Partner_Mistral_7B-GPTQ` |
|
7. The model will automatically load, and is now ready for use! |
|
8. If you want any custom settings, set them and then click **Save settings for this model** followed by **Reload the Model** in the top right. |
|
|
|
- Note that you do not need to and should not set manual GPTQ parameters any more. These are set automatically from the file `quantize_config.json`. |
|
|
|
9. Once you're ready, click the **Text Generation** tab and enter a prompt to get started! |
|
|
|
<!-- README_GPTQ.md-text-generation-webui end --> |
|
|
|
<!-- README_GPTQ.md-use-from-tgi start --> |
|
## Serving this model from Text Generation Inference (TGI) |
|
|
|
It's recommended to use TGI version 1.1.0 or later. The official Docker container is: `ghcr.io/huggingface/text-generation-inference:1.1.0` |
|
|
|
Example Docker parameters: |
|
|
|
```shell |
|
--model-id TheBloke/Writing_Partner_Mistral_7B-GPTQ --port 3000 --quantize gptq --max-input-length 3696 --max-total-tokens 4096 --max-batch-prefill-tokens 4096 |
|
``` |
|
|
|
Example Python code for interfacing with TGI (requires huggingface-hub 0.17.0 or later): |
|
|
|
```shell |
|
pip3 install huggingface-hub |
|
``` |
|
|
|
```python |
|
from huggingface_hub import InferenceClient |
|
|
|
endpoint_url = "https://your-endpoint-url-here" |
|
|
|
prompt = "Tell me about AI" |
|
prompt_template=f'''<|im_start|>system |
|
{system_message}<|im_end|> |
|
<|im_start|>user |
|
{prompt}<|im_end|> |
|
<|im_start|>assistant |
|
''' |
|
|
|
client = InferenceClient(endpoint_url) |
|
response = client.text_generation(prompt, |
|
max_new_tokens=128, |
|
do_sample=True, |
|
temperature=0.7, |
|
top_p=0.95, |
|
top_k=40, |
|
repetition_penalty=1.1) |
|
|
|
print(f"Model output: {response}") |
|
``` |
|
<!-- README_GPTQ.md-use-from-tgi end --> |
|
<!-- README_GPTQ.md-use-from-python start --> |
|
## Python code example: inference from this GPTQ model |
|
|
|
### Install the necessary packages |
|
|
|
Requires: Transformers 4.33.0 or later, Optimum 1.12.0 or later, and AutoGPTQ 0.4.2 or later. |
|
|
|
```shell |
|
pip3 install --upgrade transformers optimum |
|
# If using PyTorch 2.1 + CUDA 12.x: |
|
pip3 install --upgrade auto-gptq |
|
# or, if using PyTorch 2.1 + CUDA 11.x: |
|
pip3 install --upgrade auto-gptq --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/ |
|
``` |
|
|
|
If you are using PyTorch 2.0, you will need to install AutoGPTQ from source. Likewise if you have problems with the pre-built wheels, you should try building from source: |
|
|
|
```shell |
|
pip3 uninstall -y auto-gptq |
|
git clone https://github.com/PanQiWei/AutoGPTQ |
|
cd AutoGPTQ |
|
git checkout v0.5.1 |
|
pip3 install . |
|
``` |
|
|
|
### Example Python code |
|
|
|
```python |
|
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline |
|
|
|
model_name_or_path = "TheBloke/Writing_Partner_Mistral_7B-GPTQ" |
|
# To use a different branch, change revision |
|
# For example: revision="gptq-4bit-32g-actorder_True" |
|
model = AutoModelForCausalLM.from_pretrained(model_name_or_path, |
|
device_map="auto", |
|
trust_remote_code=False, |
|
revision="main") |
|
|
|
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True) |
|
|
|
prompt = "Tell me about AI" |
|
prompt_template=f'''<|im_start|>system |
|
{system_message}<|im_end|> |
|
<|im_start|>user |
|
{prompt}<|im_end|> |
|
<|im_start|>assistant |
|
''' |
|
|
|
print("\n\n*** Generate:") |
|
|
|
input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda() |
|
output = model.generate(inputs=input_ids, temperature=0.7, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=512) |
|
print(tokenizer.decode(output[0])) |
|
|
|
# Inference can also be done using transformers' pipeline |
|
|
|
print("*** Pipeline:") |
|
pipe = pipeline( |
|
"text-generation", |
|
model=model, |
|
tokenizer=tokenizer, |
|
max_new_tokens=512, |
|
do_sample=True, |
|
temperature=0.7, |
|
top_p=0.95, |
|
top_k=40, |
|
repetition_penalty=1.1 |
|
) |
|
|
|
print(pipe(prompt_template)[0]['generated_text']) |
|
``` |
|
<!-- README_GPTQ.md-use-from-python end --> |
|
|
|
<!-- README_GPTQ.md-compatibility start --> |
|
## Compatibility |
|
|
|
The files provided are tested to work with Transformers. For non-Mistral models, AutoGPTQ can also be used directly. |
|
|
|
[ExLlama](https://github.com/turboderp/exllama) is compatible with Llama and Mistral models in 4-bit. Please see the Provided Files table above for per-file compatibility. |
|
|
|
For a list of clients/servers, please see "Known compatible clients / servers", above. |
|
<!-- README_GPTQ.md-compatibility end --> |
|
|
|
<!-- footer start --> |
|
<!-- 200823 --> |
|
## Discord |
|
|
|
For further support, and discussions on these models and AI in general, join us at: |
|
|
|
[TheBloke AI's Discord server](https://discord.gg/theblokeai) |
|
|
|
## Thanks, and how to contribute |
|
|
|
Thanks to the [chirper.ai](https://chirper.ai) team! |
|
|
|
Thanks to Clay from [gpus.llm-utils.org](llm-utils)! |
|
|
|
I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training. |
|
|
|
If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects. |
|
|
|
Donaters will get priority support on any and all AI/LLM/model questions and requests, access to a private Discord room, plus other benefits. |
|
|
|
* Patreon: https://patreon.com/TheBlokeAI |
|
* Ko-Fi: https://ko-fi.com/TheBlokeAI |
|
|
|
**Special thanks to**: Aemon Algiz. |
|
|
|
**Patreon special mentions**: Brandon Frisco, LangChain4j, Spiking Neurons AB, transmissions 11, Joseph William Delisle, Nitin Borwankar, Willem Michiel, Michael Dempsey, vamX, Jeffrey Morgan, zynix, jjj, Omer Bin Jawed, Sean Connelly, jinyuan sun, Jeromy Smith, Shadi, Pawan Osman, Chadd, Elijah Stavena, Illia Dulskyi, Sebastain Graf, Stephen Murray, terasurfer, Edmond Seymore, Celu Ramasamy, Mandus, Alex, biorpg, Ajan Kanaga, Clay Pascal, Raven Klaugh, 阿明, K, ya boyyy, usrbinkat, Alicia Loh, John Villwock, ReadyPlayerEmma, Chris Smitley, Cap'n Zoog, fincy, GodLy, S_X, sidney chen, Cory Kujawski, OG, Mano Prime, AzureBlack, Pieter, Kalila, Spencer Kim, Tom X Nguyen, Stanislav Ovsiannikov, Michael Levine, Andrey, Trailburnt, Vadim, Enrico Ros, Talal Aujan, Brandon Phillips, Jack West, Eugene Pentland, Michael Davis, Will Dee, webtim, Jonathan Leane, Alps Aficionado, Rooh Singh, Tiffany J. Kim, theTransient, Luke @flexchar, Elle, Caitlyn Gatomon, Ari Malik, subjectnull, Johann-Peter Hartmann, Trenton Dambrowitz, Imad Khwaja, Asp the Wyvern, Emad Mostaque, Rainer Wilmers, Alexandros Triantafyllidis, Nicholas, Pedro Madruga, SuperWojo, Harry Royden McLaughlin, James Bentley, Olakabola, David Ziegler, Ai Maven, Jeff Scroggin, Nikolai Manek, Deo Leter, Matthew Berman, Fen Risland, Ken Nordquist, Manuel Alberto Morcote, Luke Pendergrass, TL, Fred von Graf, Randy H, Dan Guido, NimbleBox.ai, Vitor Caleffi, Gabriel Tamborski, knownsqashed, Lone Striker, Erik Bjäreholt, John Detwiler, Leonard Tan, Iucharbius |
|
|
|
|
|
Thank you to all my generous patrons and donaters! |
|
|
|
And thank you again to a16z for their generous grant. |
|
|
|
<!-- footer end --> |
|
|
|
# Original model card: FPHam's Writing Partner Mistral 7B |
|
|
|
|
|
<!-- header start --> |
|
<div style="display: flex; flex-direction: column; align-items: center;"> |
|
</div> |
|
<div style="width: 100%;"> |
|
<img src="https://huggingface.co/FPHam/Writing_Partner_Mistral_7B/resolve/main/writer5.jpg" alt="Writing Partner" style="width: 70%; min-width: 200px; display: block; margin: auto;"> |
|
</div> |
|
<div style="display: flex; flex-direction: column; align-items: center;"> |
|
<p><a href="https://ko-fi.com/Q5Q5MOB4M">Support me at Ko-fi</a></p> |
|
</div> |
|
<!-- header end --> |
|
|
|
|
|
Hi there! I'm your writing assistant. |
|
|
|
Think of me as your partner in crime---or rather, your partner in writing. When you hit a wall (and trust me, you will), I'll be there to knock it down for you. |
|
|
|
If you find yourself stumped, I can help you think outside the box, whether you need to figure out what happens next, develop interesting sidekicks, or create a believable love interest. And if you get stuck on names for people or places, well, that's my specialty. |
|
|
|
Just give me a shout if you have questions, need advice, or want to bounce an idea off someone. Together, we'll turn your novel into a best seller! |
|
|
|
# Intended Use |
|
|
|
The purpose of this model isn't to write content for you (although it can), but rather to engage in a conversation about your writing process. |
|
|
|
# Model uses ChatML |
|
|
|
``` |
|
<|im_start|>system |
|
<|im_end|> |
|
<|im_start|>user |
|
How to plot my story?<|im_end|> |
|
<|im_start|>assistant |
|
``` |
|
|
|
Example 1: (I had ChatGPT generate a paragraph for a sci-fi story.) |
|
|
|
Here is an opening of my story: |
|
|
|
In the distant reaches of the cosmos, where starlight weaves a tapestry of unknown wonders, Captain Alara Voss navigated her spacecraft, the Celestial Serenity, through the interstellar currents. The ship hummed with the pulsating energy of the quantum drive, propelling them toward the uncharted nebula known as the Veil of Eternity. Alara's gaze was fixed on the swirling cosmic clouds ahead, her mind ablaze with the anticipation of discovery. As the Serenity pierced the ethereal veil, the fabric of reality seemed to dance with a mysterious resonance. Little did the intrepid crew know that beyond the shimmering curtain lay a realm where time itself wove a narrative that defied mortal understanding, setting the stage for an odyssey that would reshape the boundaries of human perception. |
|
|
|
>I like this opening! It sets up some interesting questions and intrigue right off the bat. But I do think you might want to reconsider your point of view in the first paragraph. Right now it sounds more like a summary than an actual scene because there isn't any dialogue or action. Consider starting with something more immediate, perhaps from Alara's perspective. You could even begin with her looking out at the stars, thinking about what she sees. This will give us a chance to get to know her better before you launch into the big picture stuff. Here's an example: |
|
> |
|
>Alara Voss leaned against the cold metal railing of the observation deck, staring out into the infinite expanse of blackness that surrounded her ship. Stars dotted the night sky like scattered diamonds, each one a potential destination, each one a mystery waiting to be solved. She took a deep breath and let it out slowly, savoring the feeling of freedom that washed over her. It had been months since they'd left Earth, and already their journey had taken them light-years away from everything they knew. Her thoughts were interrupted by the low hum of the quantum drive kicking in, signaling that they were ready to make another jump. She watched as the stars began to blur together, forming a shimmering pathway that led the way to their next adventure. |
|
> |
|
>"Captain," came the voice of her second-in-command over the intercom. "We're entering the Veil of Eternity." |
|
> |
|
>"Thank you, Ensign," Alara replied, not taking her eyes off the swirling vortex ahead. "Let's see what lies beyond." |
|
|
|
|
|
Example 2: |
|
|
|
How to write proper dialogue? |
|
|
|
>Dialogue is a very important part of writing fiction. It's the way characters speak, and it helps define who they are. It also moves the story forward and adds tension, humor, or emotion. Dialogue must be realistic and natural-sounding, but it doesn't have to be boring. You want your readers to pay attention to what the characters are saying, so make sure that each line of dialogue counts. |
|
> |
|
>Here are some tips on how to write good dialogue: |
|
> |
|
>- Keep it short. Long speeches get tedious quickly. If one character talks for more than two sentences, break up his speech with an action or interjection from another character. |
|
> |
|
>- Use contractions (I'm, he'll). They sound more like real conversation than formal language does. |
|
> |
|
>- Vary sentence structure. This makes dialogue easier to read and understand. |
|
> |
|
>- Don't use slang unless it fits the setting or character perfectly. Slang dates easily and may not mean anything to future generations. |
|
> |
|
>- Avoid using too many adverbs in dialogue tags. Instead of "he said loudly," try something like "he bellowed." Or "she whispered." |
|
> |
|
>- Be careful not to give away too much information in dialogue tags. For example, if you say "Sarah laughed nervously," you're telling the reader she was nervous rather than showing her anxiety through her words or actions. |
|
> |
|
>- Make sure your characters don't all talk alike. Each person should have a unique voice, based on his background, education, age, gender, etc. |
|
> |
|
>- Don't forget about body language. The way someone holds himself, sits, stands, fidgets, or looks at others can add depth to a scene. |
|
> |
|
>- Use dialogue to reveal character traits and motivations. Listen carefully to people around you, and then translate those conversations onto paper. |
|
> |
|
>- Finally, remember that dialogue needs to serve a purpose in your story. Whether it advances the plot, sets the mood, or creates conflict, every word spoken by your characters should move the narrative along. |
|
|
|
|
|
|
