transformers pytorch llama text-generation unsloth axolotl exllamav2 exl2 4bit conversational en license:other autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: other
license_name: yi-license
license_link: https://huggingface.co/01-ai/Yi-34B/blob/main/LICENSE
language:
- en
pipeline_tag: text-generation
tags:
- unsloth
- axolotl
- exllamav2
- exl2
- 4bit
library_name: transformers
---

### quantized with the default exl2 dataset with sequence lengths of 8192 and 400 calibration (stage 2, optimisation) lines instead of 2048/100. possibly microwaved, presumably better.
##### resulstant measurement file is present somewhere, though the default line count of 16 (still extended to 8192) was used for measurement (stage 1)
### tokenizer works. tokenizer.model is not required for use with exllama2. no promises about sketchy software by "oobabooga"* :) try tabbyAPI/tavern, or exui if you don't miss CFG
##### consider yourselves lucky it's not a safetensors.zpaq this took all night to upload and YES i did refresh my access tokens after the Whoopsie, sorry!

###### *I'm sure it's fine it's just that I'll die if I ever see conda again.
---
# DreamGen Opus V1

<div style="display: flex; flex-direction: row; align-items: center;">
<img src="/dreamgen/opus-v1-34b/resolve/main/images/logo-1024.png" alt="model logo" style="
    border-radius: 12px;
    margin-right: 12px;
    margin-top: 0px;
    margin-bottom: 0px;
    max-width: 100px;
    height: auto;
"/>

Models for **(steerable) story-writing and role-playing**.
<br/>[All Opus V1 models, including quants](https://huggingface.co/collections/dreamgen/opus-v1-65d092a6f8ab7fc669111b31).

</div>

## Resources

- [**Opus V1 prompting guide**](https://dreamgen.com/docs/models/opus/v1) with many (interactive) examples and prompts that you can copy.
- [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing) for interactive role-play using `opus-v1.2-7b`.
- [Python code](example/prompt/format.py) to format the prompt correctly.

<img src="/dreamgen/opus-v1-34b/resolve/main/images/story_writing.webp" alt="story writing on dreamgen.com" style="
    padding: 12px;
    border-radius: 12px;
    border: 2px solid #f9a8d4;
    background: rgb(9, 9, 11);
"/>

## Prompting

<details>
<summary>The models use an extended version of ChatML.</summary>

```
<|im_start|>system
(Story description in the right format here)
(Typically consists of plot description, style description and characters)<|im_end|>
<|im_start|>user
(Your instruction on how the story should continue)<|im_end|>
<|im_start|>text names= Alice
(Continuation of the story from the Alice character)<|im_end|>
<|im_start|>text
(Continuation of the story from no character in particular (pure narration))<|im_end|>
<|im_start|>user
(Your instruction on how the story should continue)<|im_end|>
<|im_start|>text names= Bob
(Continuation of the story from the Bob character)<|im_end|>
```

The Opus V1 extension is the addition of the `text` role, and the addition / modification of role names.

Pay attention to the following:

- The `text` messages can (but don't have to have) `names`, names are used to indicate the "active" character during role-play.
- There can be multiple subsequent message with a `text` role, especially if names are involved.
- There can be multiple names attached to a message.
- The format for names is `names= {{name[0]}}; {{name[1]}}`, beware of the spaces after `names=` and after the `;`. This spacing leads to most natural tokenization for the names.
</details>

While the main goal for the models is great story-writing and role-playing performance, the models are also capable of several writing related tasks as well as general assistance.

Here's how you can prompt the model for the following tasks

- Steerable [Story-writing](https://dreamgen.com/docs/models/opus/v1#task-story-writing) and [Role-playing](https://dreamgen.com/docs/models/opus/v1#task-role-playing):
  - Input:
    - System prompt: You provide story / role-play description, which consists of:
      - Plot description
      - Style description
      - Characters and their descriptions
    - Conversation turns:
      - Text / message turn: This represents part of the story or role play
      - Instruction: This tells the model what should happen next
  - Output: Continuation of the story / role-play.
- [Story plot summarization](https://dreamgen.com/docs/models/opus/v1#task-plot-description)
  - Input: A story, or a few chapters of a story.
  - Output: A description of the story or chapters.
- [Story character description](https://dreamgen.com/docs/models/opus/v1#task-char-description)
  - Input: A story, or a few chapters of a story, set of characters.
  - Output: A description of the characters.
- [Story style description](https://dreamgen.com/docs/models/opus/v1#task-style-description)
  - Input: A story, or a few chapters of a story.
  - Output: A description the style of the story.
- [Story description to chapters](https://dreamgen.com/docs/models/opus/v1#task-story-description-to-chapter-descriptions)
  - Input: A brief plot description and the desired number of chapters.
  - Output: A description for each chapter.
- And more...

### Sampling params

For story-writing and role-play, I recommend "Min P" based sampling with `min_p` in the range `[0.01, 0.1]` and with `temperature` in the range `[0.5, 1.5]`, depending on your preferences. A good starting point would be `min_p=0.1; temperature=0.8`.

You may also benefit from setting presence, frequency and repetition penalties, especially at lower temperatures.

## Dataset

The fine-tuning dataset consisted of ~100M tokens of steerable story-writing, role-playing, writing-assistant and general-assistant examples. Each example was up to 31000 tokens long.

All story-writing and role-playing examples were based on human-written text.

![token count distribution](images/token_count_cum__token_bucket.png)

## Running the model

The model is should be compatible with any software that supports the base model, but beware of prompting and tokenization.

I recommend using these model versions:

- 7B: [no quant (opus-v1.2-7b)](https://huggingface.co/dreamgen/opus-v1.2-7b)
- 34B: [no quant (opus-v1-34b)](https://huggingface.co/dreamgen/opus-v1-34b) or [awq (opus-v1-34b-awq)](https://huggingface.co/dreamgen/opus-v1-34b-awq)

### Running on DreamGen.com (free)

You can try the model for free on [dreamgen.com](https://dreamgen.com) — note that an account is required.

### Running Locally

- **Make sure your prompt is as close as possible to the Opus V1**
  - Regardless of which backend you use, it's important that you format your prompt well and that the tokenization works correctly.
  - [Read the prompt guide](https://dreamgen.com/docs/models/opus/v1)
  - [Read the prompt formatting code](example/prompt/format.py)
  - Make sure `<|im_start|>` and `<|im_end|>` are tokenized correctly
- **vLLM**
  - [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing): This is a simple interactive Google Colab to do role-play with the 7B model, it should fit on the T4 GPU.
  - [Code](example/prompt/interactive.py): This is simple script for interactive chat for one hard-coded scenario.
- **SillyTavern**
  - [Settings](https://huggingface.co/{{REPO_ID}}/tree/main/configs/silly_tavern), v2 kindly provided by @MarinaraSpaghetti
  - [Settings screenshot](configs/silly_tavern/settings_screenshot.webp)
  - This is just an attempt at approximating the Opus V1 prompt, it won't be perfect
- **LM Studio**
  - [Config](configs/lmstudio/preset.json)
  - Just like ChatML, just changed "assistant" to "text" role.
- **HuggingFace**
  - [Chat template](tokenizer_config.json#L51)
  - Just like ChatML, just changed "assistant" to "text" role.

## Known Issues

- **34B tokenization**:
  - There seems to be a mismatch between the tokenizer of the base and fine-tuned model. It's unclear whether this also affected training, or whether it's just incorrectly saved tokenizer (you can see `tokenizer.json` was not saved ([bug report](https://github.com/OpenAccess-AI-Collective/axolotl/issues/1322))).
  - This affects BOS and EOS (which aren't really used by Yi) and the tokenization of the first input token.
  - Overall impact should be minor.
- **34B repetition**:
  - The 34B sometimes gets stuck repeating the same word, or synonyms. This seems to be a common problem across various Yi 34B fine-tunes.
- **GGUF**:
  - The conversion might be messed up and in my tests even `Q_8` of the `opus-v1.2-7b` is much worse than the `fp16` version.
- **Ooba**:
  - The tokenization might be messed up. Some users reported that `<|im_start|>` and `<|im_end|>` are tokenized as multiple tokens.

## Community

Join the DreamGen community on [**Discord**](https://dreamgen.com/discord) to get early access to new models.

## License

- This model is intended for personal use only, other use is not permitted.

---

# DreamGen Opus V1

<div style="display: flex; flex-direction: row; align-items: center;">
<img src="/dreamgen/opus-v1-34b/resolve/main/images/logo-1024.png" alt="model logo" style="
    border-radius: 12px;
    margin-right: 12px;
    margin-top: 0px;
    margin-bottom: 0px;
    max-width: 100px;
    height: auto;
"/>

Models for **(steerable) story-writing and role-playing**.
<br/>[All Opus V1 models, including quants](https://huggingface.co/collections/dreamgen/opus-v1-65d092a6f8ab7fc669111b31).

</div>

## Resources

- [**Opus V1 prompting guide**](https://dreamgen.com/docs/models/opus/v1) with many (interactive) examples and prompts that you can copy.
- [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing) for interactive role-play using `opus-v1.2-7b`.
- [Python code](example/prompt/format.py) to format the prompt correctly.

<img src="/dreamgen/opus-v1-34b/resolve/main/images/story_writing.webp" alt="story writing on dreamgen.com" style="
    padding: 12px;
    border-radius: 12px;
    border: 2px solid #f9a8d4;
    background: rgb(9, 9, 11);
"/>

## Prompting

<details>
<summary>The models use an extended version of ChatML.</summary>

```
<|im_start|>system
(Story description in the right format here)
(Typically consists of plot description, style description and characters)<|im_end|>
<|im_start|>user
(Your instruction on how the story should continue)<|im_end|>
<|im_start|>text names= Alice
(Continuation of the story from the Alice character)<|im_end|>
<|im_start|>text
(Continuation of the story from no character in particular (pure narration))<|im_end|>
<|im_start|>user
(Your instruction on how the story should continue)<|im_end|>
<|im_start|>text names= Bob
(Continuation of the story from the Bob character)<|im_end|>
```

The Opus V1 extension is the addition of the `text` role, and the addition / modification of role names.

Pay attention to the following:

- The `text` messages can (but don't have to have) `names`, names are used to indicate the "active" character during role-play.
- There can be multiple subsequent message with a `text` role, especially if names are involved.
- There can be multiple names attached to a message.
- The format for names is `names= {{name[0]}}; {{name[1]}}`, beware of the spaces after `names=` and after the `;`. This spacing leads to most natural tokenization for the names.
</details>

While the main goal for the models is great story-writing and role-playing performance, the models are also capable of several writing related tasks as well as general assistance.

Here's how you can prompt the model for the following tasks

- Steerable [Story-writing](https://dreamgen.com/docs/models/opus/v1#task-story-writing) and [Role-playing](https://dreamgen.com/docs/models/opus/v1#task-role-playing):
  - Input:
    - System prompt: You provide story / role-play description, which consists of:
      - Plot description
      - Style description
      - Characters and their descriptions
    - Conversation turns:
      - Text / message turn: This represents part of the story or role play
      - Instruction: This tells the model what should happen next
  - Output: Continuation of the story / role-play.
- [Story plot summarization](https://dreamgen.com/docs/models/opus/v1#task-plot-description)
  - Input: A story, or a few chapters of a story.
  - Output: A description of the story or chapters.
- [Story character description](https://dreamgen.com/docs/models/opus/v1#task-char-description)
  - Input: A story, or a few chapters of a story, set of characters.
  - Output: A description of the characters.
- [Story style description](https://dreamgen.com/docs/models/opus/v1#task-style-description)
  - Input: A story, or a few chapters of a story.
  - Output: A description the style of the story.
- [Story description to chapters](https://dreamgen.com/docs/models/opus/v1#task-story-description-to-chapter-descriptions)
  - Input: A brief plot description and the desired number of chapters.
  - Output: A description for each chapter.
- And more...

### Sampling params

For story-writing and role-play, I recommend "Min P" based sampling with `min_p` in the range `[0.01, 0.1]` and with `temperature` in the range `[0.5, 1.5]`, depending on your preferences. A good starting point would be `min_p=0.1; temperature=0.8`.

You may also benefit from setting presence, frequency and repetition penalties, especially at lower temperatures.

## Dataset

The fine-tuning dataset consisted of ~100M tokens of steerable story-writing, role-playing, writing-assistant and general-assistant examples. Each example was up to 31000 tokens long.

All story-writing and role-playing examples were based on human-written text.

![token count distribution](images/token_count_cum__token_bucket.png)

## Running the model

The model is should be compatible with any software that supports the base model, but beware of prompting and tokenization.

I recommend using these model versions:

- 7B: [no quant (opus-v1.2-7b)](https://huggingface.co/dreamgen/opus-v1.2-7b)
- 34B: [no quant (opus-v1-34b)](https://huggingface.co/dreamgen/opus-v1-34b) or [awq (opus-v1-34b-awq)](https://huggingface.co/dreamgen/opus-v1-34b-awq)

### Running on DreamGen.com (free)

You can try the model for free on [dreamgen.com](https://dreamgen.com) — note that an account is required.

### Running Locally

- **Make sure your prompt is as close as possible to the Opus V1**
  - Regardless of which backend you use, it's important that you format your prompt well and that the tokenization works correctly.
  - [Read the prompt guide](https://dreamgen.com/docs/models/opus/v1)
  - [Read the prompt formatting code](example/prompt/format.py)
  - Make sure `<|im_start|>` and `<|im_end|>` are tokenized correctly
- **vLLM**
  - [**Google Colab**](https://colab.research.google.com/drive/1J178fH6IdQOXNi-Njgdacf5QgAxsdT20?usp=sharing): This is a simple interactive Google Colab to do role-play with the 7B model, it should fit on the T4 GPU.
  - [Code](example/prompt/interactive.py): This is simple script for interactive chat for one hard-coded scenario.
- **SillyTavern**
  - [Settings](https://huggingface.co/{{REPO_ID}}/tree/main/configs/silly_tavern), v2 kindly provided by @MarinaraSpaghetti
  - [Settings screenshot](configs/silly_tavern/settings_screenshot.webp)
  - This is just an attempt at approximating the Opus V1 prompt, it won't be perfect
- **LM Studio**
  - [Config](configs/lmstudio/preset.json)
  - Just like ChatML, just changed "assistant" to "text" role.
- **HuggingFace**
  - [Chat template](tokenizer_config.json#L51)
  - Just like ChatML, just changed "assistant" to "text" role.

## Known Issues

- **34B tokenization**:
  - There seems to be a mismatch between the tokenizer of the base and fine-tuned model. It's unclear whether this also affected training, or whether it's just incorrectly saved tokenizer (you can see `tokenizer.json` was not saved ([bug report](https://github.com/OpenAccess-AI-Collective/axolotl/issues/1322))).
  - This affects BOS and EOS (which aren't really used by Yi) and the tokenization of the first input token.
  - Overall impact should be minor.
- **34B repetition**:
  - The 34B sometimes gets stuck repeating the same word, or synonyms. This seems to be a common problem across various Yi 34B fine-tunes.
- **GGUF**:
  - The conversion might be messed up and in my tests even `Q_8` of the `opus-v1.2-7b` is much worse than the `fp16` version.
- **Ooba**:
  - The tokenization might be messed up. Some users reported that `<|im_start|>` and `<|im_end|>` are tokenized as multiple tokens.

## Community

Join the DreamGen community on [**Discord**](https://dreamgen.com/discord) to get early access to new models.

## License

- This model is intended for personal use only, other use is not permitted.