raincandy-u/TinyChat-1776K
A tiny LM trained on TinyChat dataset from scratch.
The aim is to try to achieve natural responses on the smallest possible model. Trained using a dataset of 3 year old children level English conversations.
Note: It has no world knowledge, so you should not ask it any intellectual questions.
Model Spec
config = AutoConfig.for_model(
model_type="llama",
hidden_size=192,
intermediate_size=640,
num_attention_heads=16,
num_hidden_layers=3,
num_key_value_heads=4,
tie_word_embeddings=True,
vocab_size=2048,
max_position_embeddings=256
)
Template
<A>Hi, Tom. How are you? <end>
<B>I'm fine, thank you. And you? <end>
<A>Fine. What's your favorite color? <end>
<B>My favorite color is black. <end>
<A>Do you like cats? <end>
<B>
Example output:
Yes, I do. I like it too. They are good for me.
Generation Param
top_k=40,
top_p=0.8,
temperature=1
- Downloads last month
- 123
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.