---
license: apache-2.0
language:
- en
---
<div align="center">

# TinyMix-8x1b
</div>

This is a MoE-ification of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) 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 further train from. The intuition being finetuning 8x1b should give better performance than finetuning 1b by itself.

More work coming!

# Inference Template
This is a merge of the base model, so treat it like a completion.
```
llm.generate('Quantum Tunneling is')
```

## Mergekit Config
```
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
gate_mode: hidden
dtype: bfloat16
experts:
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
  - source_model: /TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
    positive_prompts: [""]
```

# Eval
Thanks to u/mhenrichsen for thr HellaSwag score

```
|  Tasks  |Version|Filter|n-shot| Metric |Value |   |Stderr|

|---------|-------|------|-----:|--------|-----:|---|-----:|

|hellaswag|Yaml   |none  |     0|acc     |0.4659|±  |0.0050|

|         |       |none  |     0|acc\_norm|0.6044|±  |0.0049|  

```