---
license: apache-2.0
datasets:
- HuggingFaceTB/cosmopedia
- databricks/databricks-dolly-15k
- Open-Orca/OpenOrca
language:
- en
metrics:
- accuracy
library_name: transformers
pipeline_tag: text-generation
---

# WikiChat-v0.2
Training in progress model to have conversations.

The GGUFs uploaded are full FP32 precision.

Using OpenOrca GPT-4 data + cosmopedia for some extra data + dolly15k for instruct

## Model Details:
- 83.59M parameters (83591800)
- 8 attention heads
- 40 layers
- 384 embeddings size
- 4096/8192/16384 context (please use 2/4x RoPE scaling, may train a 16k finetuned version later)
- Batch size 16
- llama.cpp (train-text-from-scratch)

## Prompt Format (Alpaca):
```
Instruction: {system}
Input: {prompt}
Response: {response}
```

Please structure your prompts in an instruct format for maximum performance.

## Training Details:
- 1x RTX 3070 8GB (Infrencing speed: 80tok/s, full GPU offload)
- 1x Ryzen 3 3700x
- 96gb RAM
- 10 iterations
- Loss Target = 2.5 to 3.0
- Approx 480 samples/1M train tokens (>0.0001 epoches)
- Training data = Refer to OpenOrca page

## Notes:

The model isn't ready yet; this is to test tokenization of OpenOrca and a balance between training speed and model size

## Example output:
```
User: What is the square root of 4?
```
```
Assistant: The square root of 4 is 2.
```