cyente commited on
Commit
acb224f
·
verified ·
1 Parent(s): 51df6bb

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +1 -3
README.md CHANGED
@@ -22,8 +22,6 @@ Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (
22
 
23
  - Significantly improvements in **code generation**, **code reasoning** and **code fixing**. Base on the strong Qwen2.5, we scale up the training tokens into 5.5 trillion including source code, text-code grounding, Synthetic data, etc. Qwen2.5-Coder-32B has become the current state-of-the-art open-source codeLLM, with its coding abilities matching those of GPT-4o.
24
  - A more comprehensive foundation for real-world applications such as **Code Agents**. Not only enhancing coding capabilities but also maintaining its strengths in mathematics and general competencies.
25
- - **Long-context Support** up to 128K tokens.
26
-
27
 
28
  **This repo contains the 1.5B Qwen2.5-Coder model**, which has the following features:
29
  - Type: Causal Language Models
@@ -33,7 +31,7 @@ Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (
33
  - Number of Paramaters (Non-Embedding): 1.31B
34
  - Number of Layers: 28
35
  - Number of Attention Heads (GQA): 12 for Q and 2 for KV
36
- - Context Length: Full 131,072 tokens
37
  - Please refer to [this section](#processing-long-texts) for detailed instructions on how to deploy Qwen2.5 for handling long texts.
38
 
39
  **We do not recommend using base language models for conversations.** Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., or fill in the middle tasks on this model.
 
22
 
23
  - Significantly improvements in **code generation**, **code reasoning** and **code fixing**. Base on the strong Qwen2.5, we scale up the training tokens into 5.5 trillion including source code, text-code grounding, Synthetic data, etc. Qwen2.5-Coder-32B has become the current state-of-the-art open-source codeLLM, with its coding abilities matching those of GPT-4o.
24
  - A more comprehensive foundation for real-world applications such as **Code Agents**. Not only enhancing coding capabilities but also maintaining its strengths in mathematics and general competencies.
 
 
25
 
26
  **This repo contains the 1.5B Qwen2.5-Coder model**, which has the following features:
27
  - Type: Causal Language Models
 
31
  - Number of Paramaters (Non-Embedding): 1.31B
32
  - Number of Layers: 28
33
  - Number of Attention Heads (GQA): 12 for Q and 2 for KV
34
+ - Context Length: Full 32,768 tokens
35
  - Please refer to [this section](#processing-long-texts) for detailed instructions on how to deploy Qwen2.5 for handling long texts.
36
 
37
  **We do not recommend using base language models for conversations.** Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., or fill in the middle tasks on this model.