Korbinian Pöppel commited on
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90f1e33
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1 Parent(s): 7746361

Fix: Typo.

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  1. README.md +4 -5
README.md CHANGED
@@ -2,8 +2,8 @@
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  license: other
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  ---
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- # xLSTM goes 7B
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- This xLSTM was pre-trained on the DCLM and selected high-quality data for in a total of approx. 2.3 T tokens using the `xlstm-jax` framework.
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  ## How to use it
@@ -26,13 +26,13 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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  xlstm = AutoModelForCausalLM.from_pretrained("NX-AI/xLSTM-7b", device_map="auto")
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  # this is a fork of EleutherAI/gpt-neox-20b
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- tokenizers = AutoTokenizer.from_pretrained("NX-AI/xLSTM-7b")
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  xlstm(tokenizer("Hello xLSTM, how are you doing?"))
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  ```
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  ## Speed results
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- Generation Speed using `torch.cuda.graph` and `torch.compile` optimizations:
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  ![generation speed](plot_tokens_per_sec.svg)
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  ## Performance
@@ -52,4 +52,3 @@ Using HuggingFace's `lighteval` in the Leaderboard-v1 settings:
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  ## License
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  NXAI Community License (see `LICENSE` file)
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-
 
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  license: other
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  ---
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+ # xLSTM-7B
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+ This xLSTM-7B was pre-trained on the DCLM and selected high-quality data for in a total of approx. 2.3 T tokens using the `xlstm-jax` framework.
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  ## How to use it
 
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  xlstm = AutoModelForCausalLM.from_pretrained("NX-AI/xLSTM-7b", device_map="auto")
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  # this is a fork of EleutherAI/gpt-neox-20b
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+ tokenizer = AutoTokenizer.from_pretrained("NX-AI/xLSTM-7b")
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  xlstm(tokenizer("Hello xLSTM, how are you doing?"))
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  ```
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  ## Speed results
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+ Generation Speed using `torch.cuda.graph` and `torch.compile` optimizations on one NVIDIA H100:
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  ![generation speed](plot_tokens_per_sec.svg)
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  ## Performance
 
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  ## License
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  NXAI Community License (see `LICENSE` file)