Update README.md

README.md

@@ -2,7 +2,7 @@
 license: other
 license_name: katanemo-research
 license_link: >-
-  https://huggingface.co/katanemolabs/Arch-Function-Calling-1.5B/blob/main/LICENSE
+  https://huggingface.co/katanemolabs/Arch-Function-1.5B/blob/main/LICENSE
 base_model:
 - Qwen/Qwen2.5-1.5B-Instruct
 language:
@@ -11,12 +11,12 @@ pipeline_tag: text-generation
 library_name: transformers
 ---
 
-# Katanemo/Arch-Function-Calling-1.5B
+# katanemolabs/Arch-Function-1.5B
 
 ## Overview
-The Katanemo Arch-Function-Calling collection of large language models (LLMs) is a collection state-of-the-art (SOTA) LLMs specifically designed for **function calling** tasks. The models are designed to understand complex function signatures, identify required parameters, and produce accurate function call outputs based on natural language prompts. Achieving performance on par with GPT-4, these models set a new benchmark in the domain of function-oriented tasks, making them suitable for scenarios where automated API interaction and function execution is crucial.
+The Katanemo Arch-Function collection of large language models (LLMs) is a collection state-of-the-art (SOTA) LLMs specifically designed for **function calling** tasks. The models are designed to understand complex function signatures, identify required parameters, and produce accurate function call outputs based on natural language prompts. Achieving performance on par with GPT-4, these models set a new benchmark in the domain of function-oriented tasks, making them suitable for scenarios where automated API interaction and function execution is crucial.
 
-In summary, the Katanemo Arch-Function-Calling collection demonstrates:
+In summary, the Katanemo Arch-Function collection demonstrates:
 - **State-of-the-art performance** in function calling
 - **Accurate parameter identification and suggestion**, even in ambiguous or incomplete inputs
 - **High generalization** across multiple function calling use cases, from API interactions to automated backend tasks.
@@ -49,11 +49,11 @@ In summary, the Katanemo Arch-Function-Calling collection demonstrates:
 
 
 ## Training Details
-Katanemo Arch-Function-Calling collection is built on top of the [Qwen 2.5](https://huggingface.co/collections/Qwen/qwen25-66e81a666513e518adb90d9e). A blog with technical details leading to our models will be published soon.
+Katanemo Arch-Function collection is built on top of the [Qwen 2.5](https://huggingface.co/collections/Qwen/qwen25-66e81a666513e518adb90d9e). A blog with technical details leading to our models will be published soon.
 
 
 ## Performance Benchmarks
-We evaluate Katanemo Arch-Function-Calling series on the [Berkeley Function-Calling Leaderboard (BFCL)](https://gorilla.cs.berkeley.edu/leaderboard.html#leaderboard). For each model family, we select the one with the highest rank. The results are shwon below:
+We evaluate Katanemo Arch-Function series on the [Berkeley Function-Calling Leaderboard (BFCL)](https://gorilla.cs.berkeley.edu/leaderboard.html#leaderboard). For each model family, we select the one with the highest rank. The results are shwon below:
 
 <table>
   <tr style="text-align: center; vertical-align: middle; font-weight: bold;">
@@ -96,7 +96,7 @@ We evaluate Katanemo Arch-Function-Calling series on the [Berkeley Function-Call
   </tr>
   <tr style="text-align: center; vertical-align: middle; font-weight: bold;">
     <td> </td>
-    <td>Arch-Function-Calling-7B</td>
+    <td>Arch-Function-7B</td>
     <td>57.48%</td>
     <td>87.50%</td>
     <td>86.80%</td>
@@ -107,7 +107,7 @@ We evaluate Katanemo Arch-Function-Calling series on the [Berkeley Function-Call
   </tr>
   <tr style="text-align: center; vertical-align: middle; font-weight: bold;">
     <td> </td>
-    <td>Arch-Function-Calling-3B</td>
+    <td>Arch-Function-3B</td>
     <td>56.23%</td>
     <td>85.10%</td>
     <td>89.16%</td>
@@ -141,7 +141,7 @@ We evaluate Katanemo Arch-Function-Calling series on the [Berkeley Function-Call
   </tr>
   <tr style="text-align: center; vertical-align: middle; font-weight: bold;">
     <td> </td>
-    <td>Arch-Function-Calling-1.5B</td>
+    <td>Arch-Function-1.5B</td>
     <td>53.61%</td>
     <td>82.60%</td>
     <td>87.36%</td>
@@ -176,7 +176,7 @@ We evaluate Katanemo Arch-Function-Calling series on the [Berkeley Function-Call
 
 
 # Requirements
-The code of Arch-Function-Calling-1.5B has been in the Hugging Face `transformers` library and we advise you to install latest version:
+The code of Arch-Function-1.5B has been in the Hugging Face `transformers` library and we advise you to install latest version:
 ```bash
 pip install transformers>=4.37.0
 ```
@@ -192,7 +192,7 @@ import json
 from typing import Any, Dict, List
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_name = "katanemolabs/Arch-Function-Calling-1.5B"
+model_name = "katanemolabs/Arch-Function-1.5B"
 model = AutoModelForCausalLM.from_pretrained(
     model_name, device_map="auto", torch_dtype="auto", trust_remote_code=True
 )
@@ -332,4 +332,4 @@ The current temperature in Seattle is 62 degrees in Fahrenheit.
 
 
 # License
-Katanemo Arch-Function-Calling collection is distributed under the [Katanemo license](https://huggingface.co/katanemolabs/Arch-Function-Calling-1.5B/blob/main/LICENSE).
+Katanemo Arch-Function collection is distributed under the [Katanemo license](https://huggingface.co/katanemolabs/Arch-Function-1.5B/blob/main/LICENSE).