File size: 1,765 Bytes
cc2bd6e 060f027 cc2bd6e |
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 |
---
license: apache-2.0
language:
- en
---
<div align="center">
# TinyMix-8x1b-Chat
</div>
This is a MoE-ification of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) using the [Mixtral branch of mergekit](https://github.com/cg123/mergekit)
The Goal was to MoE-fy the TinyLlama model and then use this as a base model to finetune from. The intuition being finetuning 8x1b should give better performance than finetuning 1b by itself.
More work coming!
# Chat Template
```
def make_prompt(instruction):
return f"<|im_start|>user\n{instruction}<|im_end|>\n<|im_start|>assistant\n"
llm.generate(make_prompt('What is quantum tunneling?'))
```
## Mergekit Config
```
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
- source_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
positive_prompts: [""]
```
# Eval
Thanks to u/mhenrichsen for the HellaSwag score
```
| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
|---------|-------|------|-----:|--------|-----:|---|-----:|
|hellaswag|Yaml |none | 0|acc |0.4657|± |0.0050|
| | |none | 0|acc\_norm|0.6042|± |0.0049|
``` |