Qwen-7B VS ToolBench

Compare Qwen-7B vs ToolBench and see what are their differences.

Qwen-7B

The official repo of Qwen (通义千问) chat & pretrained large language model proposed by Alibaba Cloud. [Moved to: https://github.com/QwenLM/Qwen] (by QwenLM)

ToolBench

[ICLR'24 spotlight] An open platform for training, serving, and evaluating large language model for tool learning. (by OpenBMB)
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Qwen-7B ToolBench
2 3
5,030 4,455
- 4.2%
8.3 8.3
8 months ago 6 days ago
Python Python
GNU General Public License v3.0 or later Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Qwen-7B

Posts with mentions or reviews of Qwen-7B. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-07.

ToolBench

Posts with mentions or reviews of ToolBench. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-07.

What are some alternatives?

When comparing Qwen-7B and ToolBench you can also consider the following projects:

SqueezeLLM - [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization

gorilla-cli - LLMs for your CLI

EverythingApacheNiFi - EverythingApacheNiFi

NiFi-Man - Like Travel Man, But With Data. The Data is Here, But Should We Have Ingested it?

harlequin - The SQL IDE for Your Terminal.

fuzzy-matcher - A Java library to determine probability of objects being similar.

flink-kubernetes-operator - Apache Flink Kubernetes Operator

anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.