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
- 83
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.