Text Generation
Transformers
PyTorch
Safetensors
gpt2
conversational
text-generation-inference
Inference Endpoints
Ekgren commited on
Commit
8cab4ac
1 Parent(s): b9b4119

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +1 -1
README.md CHANGED
@@ -3,7 +3,7 @@ license: other
3
  ---
4
  # Model description
5
  [AI Sweden](https://huggingface.co/AI-Sweden/)
6
- [GPT-Sw3 126M](https://huggingface.co/AI-Sweden-Models/gpt-sw3-126m/) | [GPT-Sw3 356M](https://huggingface.co/AI-Sweden-Models/gpt-sw3-356m/) | [GPT-Sw3 1.3B](https://huggingface.co/AI-Sweden-Models/gpt-sw3-1.3b/) | [GPT-Sw3 6.7B](https://huggingface.co/AI-Sweden-Models/gpt-sw3-6.7b/) | [GPT-Sw3 20B](https://huggingface.co/AI-Sweden-Models/gpt-sw3-20b/) | [GPT-Sw3 40B](https://huggingface.co/AI-Sweden-Models/gpt-sw3-40b/)
7
 
8
  GPT-SW3 is a collection of large decoder-only pretrained transformer language models that were developed by AI Sweden in collaboration with RISE and the WASP WARA for Media and Language. GPT-SW3 has been trained on a dataset containing 320B tokens in Swedish, Norwegian, Danish, Icelandic, English, and programming code. The model was pretrained using a causal language modeling (CLM) objective utilizing the NeMo Megatron GPT implementation.
9
 
 
3
  ---
4
  # Model description
5
  [AI Sweden](https://huggingface.co/AI-Sweden/)
6
+ [GPT-Sw3 126M instruct](https://huggingface.co/AI-Sweden-Models/gpt-sw3-126m-instruct/) | [GPT-Sw3 356M instruct](https://huggingface.co/AI-Sweden-Models/gpt-sw3-356m/) | [GPT-Sw3 1.3B instruct](https://huggingface.co/AI-Sweden-Models/gpt-sw3-1.3b-instruct/) | [GPT-Sw3 6.7B instruct](https://huggingface.co/AI-Sweden-Models/gpt-sw3-6.7b-instruct/) | [GPT-Sw3 20B instruct](https://huggingface.co/AI-Sweden-Models/gpt-sw3-20b-instruct/)
7
 
8
  GPT-SW3 is a collection of large decoder-only pretrained transformer language models that were developed by AI Sweden in collaboration with RISE and the WASP WARA for Media and Language. GPT-SW3 has been trained on a dataset containing 320B tokens in Swedish, Norwegian, Danish, Icelandic, English, and programming code. The model was pretrained using a causal language modeling (CLM) objective utilizing the NeMo Megatron GPT implementation.
9