File size: 2,360 Bytes
82f85af 6ef240c 82f85af fe775a0 82f85af 694b18c 6ef240c 82f85af 561824f 82f85af 2b2b80b 561824f 12a0a41 82f85af eb0f531 82f85af eb0f531 82f85af 6ef240c 41ebf69 82f85af eb0f531 82f85af |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
base_model:
- Qwen/Qwen2.5-72B
tags:
- roleplay
- storywriting
- qwen2.5
- finetune
- transformers
- pytorch
---
# Zeus Labs ~ Chronos-Platinum-72B
Qwen 2.5 72B base model, trained for two epochs on the Chronos Divergence dataset using ChatML. It works well for roleplaying and storywriting as well as general assistant tasks.
## Instruct Template
This model uses `ChatML` - below is an example. It is a preset in many frontends.
```
<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
Hello there!<|im_end|>
<|im_start|>assistant
Hi! I'm an AI assistant, designed to help people like you with all sorts of tasks. Is there anything you need help with?<|im_end|>
<|im_start|>user
I was wondering how transformers work?<|im_end|>
<|im_start|>assistant
```
## Quantization
Please note that we tested this model with a 5.0bpw EXL2 quant. Results are not expected to be the same when going below this quanitzation. Thanks to our model quanters!
#### LlamaCPP (GGUF)
[bartowski](https://huggingface.co/bartowski/Chronos-Platinum-72B-GGUF)
[mradermacher - imatrix](https://huggingface.co/mradermacher/Chronos-Platinum-72B-i1-GGUF)
#### Exllama2
TODO!
#### FP8
TODO!
## Sampling Settings
Here are some settings that work well with this model:
```
Coming soon
```
## Credit
Thank you to my team consisting of [@ToastyPigeon](https://huggingface.co/ToastyPigeon), [@Fizzarolli](https://huggingface.co/Fizzarolli), and myself [@elinas](https://huggingface.co/elinas).
Additional thanks to [@AlpinDale](https://huggingface.co/AlpinDale) and the rest of the PygmalionAI team for graciously providing the compute to finetune this model!
Thank you to [anthracite-org](https://huggingface.co/anthracite-org) as well for sponsoring this model.
## Additional Details
We used a combination of provided logs and WizardLM evol both cleaned up and de-slopped.
Thanks to Anthropic and OpenAI for the models used to generate synthetic and partially synthetic data to train this model.
Thanks Elon Musk for being based enough to train AI that compares to the top models.
If you have any questions or concerns, please post in the community tab.
DISCLAIMER: Outputs generated by the model are not reflective of our views. |