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weblab-10b

Text Generation
Transformers
PyTorch
gpt_neox
Inference Endpoints
text-generation-inference
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Takeshi Kojima commited on
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  license: cc-by-nc-4.0
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  ---
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- # tsubaki-10b
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  # Overview
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  This repository provides a Japanese-centric multilingual GPT-NeoX model of 10 billion parameters.
@@ -26,8 +26,8 @@ This repository provides a Japanese-centric multilingual GPT-NeoX model of 10 bi
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  | Variant | Link |
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  | :-- | :--|
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- | tsubaki-10b-instruction-sft | https://huggingface.co/Kojima777/tsubaki-10b-instruction-sft |
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- | tsubaki-10b | https://huggingface.co/Kojima777/tsubaki-10b |
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  * **Authors**
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@@ -43,8 +43,8 @@ This repository provides a Japanese-centric multilingual GPT-NeoX model of 10 bi
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  | Model | Average | JCommonsenseQA | JNLI | MARC-ja | JSQuAD |
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  | :-- | :-- | :-- | :-- | :-- | :-- |
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- | tsubaki-10b-instruction-sft | 79.04 | 74.35 | 65.65 | 96.06 | 80.09 |
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- | tsubaki-10b | 67.27 | 65.86 | 54.19 | 84.49 | 64.54 |
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  ---
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@@ -54,8 +54,8 @@ This repository provides a Japanese-centric multilingual GPT-NeoX model of 10 bi
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  import torch
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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- tokenizer = AutoTokenizer.from_pretrained("Kojima777/tsubaki-10b", use_fast=False)
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- model = AutoModelForCausalLM.from_pretrained("Kojima777/tsubaki-10b")
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  if torch.cuda.is_available():
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  model = model.to("cuda")
 
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  license: cc-by-nc-4.0
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  ---
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+ # weblab-10b
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  # Overview
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  This repository provides a Japanese-centric multilingual GPT-NeoX model of 10 billion parameters.
 
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  | Variant | Link |
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  | :-- | :--|
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+ | weblab-10b-instruction-sft | https://huggingface.co/Kojima777/weblab-10b-instruction-sft |
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+ | weblab-10b | https://huggingface.co/Kojima777/weblab-10b |
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  * **Authors**
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  | Model | Average | JCommonsenseQA | JNLI | MARC-ja | JSQuAD |
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  | :-- | :-- | :-- | :-- | :-- | :-- |
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+ | weblab-10b-instruction-sft | 79.04 | 74.35 | 65.65 | 96.06 | 80.09 |
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+ | weblab-10b | 67.27 | 65.86 | 54.19 | 84.49 | 64.54 |
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  ---
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  import torch
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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+ tokenizer = AutoTokenizer.from_pretrained("Kojima777/weblab-10b", use_fast=False)
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+ model = AutoModelForCausalLM.from_pretrained("Kojima777/weblab-10b")
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  if torch.cuda.is_available():
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  model = model.to("cuda")