Update README.md

README.md

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 #### Introducing palmer-004
 
-We are thrilled to unveil palmer-004, the fourth iteration in our esteemed palmer series, designed to push the boundaries of performance and context window capacity. Merging the best of palmer-003 with the expansive capabilities of palmer-002-32k, palmer-004 is a testament to the power of merging similar trained models, think of it as palmer-003 with 32k context and low performance degradation.
+We are thrilled to unveil palmer-004, the fourth iteration in our esteemed palmer series, designed to push the boundaries of performance and context window capacity. Merging the best of palmer-003 with the expansive capabilities of palmer-002-32k, palmer-004 is a testament to the power of merging similar trained models, think of it as palmer-003 with 32k context with minimal performance degradation.
 
 | Model         | MMLU  | ARC-C | HellaSwag | PIQA   | Winogrande |
 |---------------|-------|-------|-----------|--------|------------|