prithivMLmods/Calcium-Opus-14B-Elite-Stock
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Calcium-Opus-14B-Elite-Stock/README.md
ModelHub XC 1fe382157b 初始化项目，由ModelHub XC社区提供模型 
Model: prithivMLmods/Calcium-Opus-14B-Elite-Stock
Source: Original Platform
2026-06-04 17:30:14 +08:00

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base_model, library_name, tags, model-index
base_model library_name tags model-index
prithivMLmods/Calcium-Opus-14B-Elite
prithivMLmods/Calcium-Opus-14B-Elite4
prithivMLmods/Calcium-Opus-14B-Elite3
prithivMLmods/Calcium-Opus-14B-Elite2
transformers
mergekit
merge
name results
Calcium-Opus-14B-Elite-Stock
task dataset metrics source
type name
text-generation Text Generation
name type split args
IFEval (0-Shot) wis-k/instruction-following-eval train
num_few_shot
0
type value name
inst_level_strict_acc and prompt_level_strict_acc 61.43 averaged accuracy
url name
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FCalcium-Opus-14B-Elite-Stock Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type split args
BBH (3-Shot) SaylorTwift/bbh test
num_few_shot
3
type value name
acc_norm 46.9 normalized accuracy
url name
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FCalcium-Opus-14B-Elite-Stock Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type split args
MATH Lvl 5 (4-Shot) lighteval/MATH-Hard test
num_few_shot
4
type value name
exact_match 27.19 exact match
url name
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FCalcium-Opus-14B-Elite-Stock Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type split args
GPQA (0-shot) Idavidrein/gpqa train
num_few_shot
0
type value name
acc_norm 15.77 acc_norm
url name
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FCalcium-Opus-14B-Elite-Stock Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type args
MuSR (0-shot) TAUR-Lab/MuSR
num_few_shot
0
type value name
acc_norm 20.06 acc_norm
url name
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FCalcium-Opus-14B-Elite-Stock Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
MMLU-PRO (5-shot) TIGER-Lab/MMLU-Pro main test
num_few_shot
5
type value name
acc 47.6 accuracy
url name
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FCalcium-Opus-14B-Elite-Stock Open LLM Leaderboard

Calcium-Opus-14B-Elite-Stock

Calcium-Opus-14B-Elite is based on the Qwen 2.5 14B modality architecture, designed to enhance the reasoning capabilities of 14B-parameter models. These models have proven effective in context understanding, reasoning, and mathematical problem-solving.It has been fine-tuned using a long chain-of-thought reasoning model and specialized datasets, with a focus on chain-of-thought (CoT) reasoning for problem-solving. This model is optimized for tasks requiring logical reasoning, detailed explanations, and multi-step problem-solving, making it ideal for applications such as instruction-following, text generation, and complex reasoning tasks.

merge

This is a merge of pre-trained language models created using mergekit.

Merge Method

This model was merged using the Model Stock merge method using prithivMLmods/Calcium-Opus-14B-Elite as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: prithivMLmods/Calcium-Opus-14B-Elite
  - model: prithivMLmods/Calcium-Opus-14B-Elite2
  - model: prithivMLmods/Calcium-Opus-14B-Elite3
  - model: prithivMLmods/Calcium-Opus-14B-Elite4
merge_method: model_stock
base_model: prithivMLmods/Calcium-Opus-14B-Elite
parameters:
  normalize: false
  int8_mask: true
dtype: bfloat16
tokenizer_source: "prithivMLmods/Calcium-Opus-14B-Elite"

Open LLM Leaderboard Evaluation Results

Detailed results can be found here! Summarized results can be found here!

Metric Value (%)
Average 36.49
IFEval (0-Shot) 61.43
BBH (3-Shot) 46.90
MATH Lvl 5 (4-Shot) 27.19
GPQA (0-shot) 15.77
MuSR (0-shot) 20.06
MMLU-PRO (5-shot) 47.60