Update README.md

README.md

@@ -222,7 +222,8 @@ The uploaded version on Hugging Face retains the bf16 format for public use.
 
 Designed for integration into professional developer tooling (e.g., intelligent code suggestions in IDEs), AI-powered coding assistants, and research on code understanding and generation, Mellum is also well-suited for educational applications and fine-tuning experiments.
 
-This release includes a base model, and some SFT models as well. 
+This release includes a base model, and Python SFT models as well. 
+Models for other languages will be released soon.
 Keep in mind that base model is not fine-tuned for downstream tasks out-of-the-box, however, it is fully capable of supporting supervised fine-tuning (SFT) and reinforcement learning (RL) for adaptation to specific applications.
 
 # Training Data
@@ -266,6 +267,8 @@ Since Mellum has a maximum context window of 8k, we report here both the average
 | Mellum-4b-sft-python | 33.16%      | 36.11%  | 57.10% | 42.12%  |
 | Mellum-4b-base       | 25.30%      | 38.39%  | 50.65% | 38.11%  |
 
+We are investigating potential issues with SAFIM evaluation.
+
 ## HumanEval Infilling
 - Type: single-line and multi-line
 - Languages: Python