---
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|
```