# Description

This is my first attempt to simulate the Filian's Twitch stream chat based on scraped data. The model is a fine-tuning of GPT-Neo for 125M parameters. The model was able to be trained within 30 minutes on a GTX 1650 with Pytorch's memory pinning feature to share the local RAM with the GPU.

# Usage

Make sure to include the prefix "STREAMER: " at the end of the prompt or anywhere the response of the streamer is supposed to go. "Chat messages" are prepend with the "CHAT: " keyword.
In case the Hosted Inference API (text box on the side) gets too little text, just keep pressing "Compute" until the sentence ends.

## Prompt examples
```
CHAT: You're cringe
CHAT: KEKW
STREAMER:
```
```
CHAT: Are you a Filipino boy?
STREAMER: 
```

```
CHAT: Hello
CHAT: KEKW Filian is cringe
STREAMER: 
```

Using the keyword "STREAM TITLE" will attempt to replicate the name of a stream:

```
STREAM TITLE: 
```

You can also induce the streamer to say something by adding a few words of your own at the beginning:

```
STREAM: Today we will
```
{"language": ["en"], "license": "gpl", "tags": ["twitch"], "datasets": ["Differentiable/processed_chats"]}
transformers pytorch gpt_neo text-generation twitch en dataset:Differentiable/processed_chats license:gpl autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #gpt_neo #text-generation #twitch #en #dataset-Differentiable/processed_chats #license-gpl #autotrain_compatible #endpoints_compatible #region-us 

# Description

This is my first attempt to simulate the Filian's Twitch stream chat based on scraped data. The model is a fine-tuning of GPT-Neo for 125M parameters. The model was able to be trained within 30 minutes on a GTX 1650 with Pytorch's memory pinning feature to share the local RAM with the GPU.

# Usage

Make sure to include the prefix "STREAMER: " at the end of the prompt or anywhere the response of the streamer is supposed to go. "Chat messages" are prepend with the "CHAT: " keyword.
In case the Hosted Inference API (text box on the side) gets too little text, just keep pressing "Compute" until the sentence ends.

## Prompt examples





Using the keyword "STREAM TITLE" will attempt to replicate the name of a stream:



You can also induce the streamer to say something by adding a few words of your own at the beginning:


# Description

This is my first attempt to simulate the Filian's Twitch stream chat based on scraped data. The model is a fine-tuning of GPT-Neo for 125M parameters. The model was able to be trained within 30 minutes on a GTX 1650 with Pytorch's memory pinning feature to share the local RAM with the GPU. # Usage

Make sure to include the prefix "STREAMER: " at the end of the prompt or anywhere the response of the streamer is supposed to go. "Chat messages" are prepend with the "CHAT: " keyword.
In case the Hosted Inference API (text box on the side) gets too little text, just keep pressing "Compute" until the sentence ends. ## Prompt examples





Using the keyword "STREAM TITLE" will attempt to replicate the name of a stream:



You can also induce the streamer to say something by adding a few words of your own at the beginning:
TAGS
#transformers #pytorch #gpt_neo #text-generation #twitch #en #dataset-Differentiable/processed_chats #license-gpl #autotrain_compatible #endpoints_compatible #region-us 
 # Description

This is my first attempt to simulate the Filian's Twitch stream chat based on scraped data. The model is a fine-tuning of GPT-Neo for 125M parameters. The model was able to be trained within 30 minutes on a GTX 1650 with Pytorch's memory pinning feature to share the local RAM with the GPU. # Usage

Make sure to include the prefix "STREAMER: " at the end of the prompt or anywhere the response of the streamer is supposed to go. "Chat messages" are prepend with the "CHAT: " keyword.
In case the Hosted Inference API (text box on the side) gets too little text, just keep pressing "Compute" until the sentence ends. ## Prompt examples





Using the keyword "STREAM TITLE" will attempt to replicate the name of a stream:



You can also induce the streamer to say something by adding a few words of your own at the beginning:
TAGS
#transformers #pytorch #gpt_neo #text-generation #twitch #en #dataset-Differentiable/processed_chats #license-gpl #autotrain_compatible #endpoints_compatible #region-us 
# Description

This is my first attempt to simulate the Filian's Twitch stream chat based on scraped data. The model is a fine-tuning of GPT-Neo for 125M parameters. The model was able to be trained within 30 minutes on a GTX 1650 with Pytorch's memory pinning feature to share the local RAM with the GPU.# Usage

Make sure to include the prefix "STREAMER: " at the end of the prompt or anywhere the response of the streamer is supposed to go. "Chat messages" are prepend with the "CHAT: " keyword.
In case the Hosted Inference API (text box on the side) gets too little text, just keep pressing "Compute" until the sentence ends.## Prompt examples





Using the keyword "STREAM TITLE" will attempt to replicate the name of a stream:



You can also induce the streamer to say something by adding a few words of your own at the beginning: