Update README.md

README.md

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 tags: []
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-# Jamba-Small v1
-
-This is a pruned version of AI21 Labs' Jamba-v0.1 model that is ~25% the size of Jamba-v0.1.
-
-
-
-## Model Details
-Whereas Jamba-v0.1 contains 4 Jamba blocks, Jamba-Small contains only 1 Jamba block.
-Jamba-Small's Jamba blocks follow the same structure seen in Jamba-v0.1, with a 1:7 ratio of attention-to-Mamba layers and MoE applied every 2 layers.
-
-Jamba-Small's weights are initialized from various layers in the original Jamba-v0.1 model. For v1, the layer weights are mapped as follows (left is Jamba-Small layer number, right is Jamba-v0.1 layer number):
-```
-0: 0
-1: 1
-2: 2
-3: 3
-4: 4
-5: 5
-6: 30
-7: 31
-```
-
-Note that no additional fine-tuning has been performed on this model. As such, its performance is exceptionally poor. This should not be used in production without additional training.
-
-### Model Description
-
-- **Developed by:** Nathan Brown (OxxoCodes)
-- **Compute provided by:** Clemson Palmetto Cluster
-- **Model type:** Joint Attention and Mamba (Jamba)
-- **Language(s) (NLP):** English
-- **License:** Apache 2.0
-- **Original model:** [Jamba-v0.1](https://huggingface.co/ai21labs/Jamba-v0.1)
-- **Jamba paper:** [https://arxiv.org/pdf/2403.19887.pdf](https://arxiv.org/pdf/2403.19887.pdf)
+# Jamba-13B