Instructions to use prithivMLmods/Calcium-Opus-14B-Elite2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use prithivMLmods/Calcium-Opus-14B-Elite2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="prithivMLmods/Calcium-Opus-14B-Elite2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/Calcium-Opus-14B-Elite2")
model = AutoModelForCausalLM.from_pretrained("prithivMLmods/Calcium-Opus-14B-Elite2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use prithivMLmods/Calcium-Opus-14B-Elite2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "prithivMLmods/Calcium-Opus-14B-Elite2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Calcium-Opus-14B-Elite2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/prithivMLmods/Calcium-Opus-14B-Elite2

SGLang

How to use prithivMLmods/Calcium-Opus-14B-Elite2 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "prithivMLmods/Calcium-Opus-14B-Elite2" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Calcium-Opus-14B-Elite2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "prithivMLmods/Calcium-Opus-14B-Elite2" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Calcium-Opus-14B-Elite2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use prithivMLmods/Calcium-Opus-14B-Elite2 with Docker Model Runner:
```
docker model run hf.co/prithivMLmods/Calcium-Opus-14B-Elite2
```

Adding Evaluation Results

by prithivMLmods - opened Feb 21, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

+15

-0

Files changed (1) hide show

README.md +15 -0

README.md CHANGED Viewed

@@ -216,3 +216,18 @@ Summarized results can be found [here](https://huggingface.co/datasets/open-llm-
 |MuSR (0-shot)      |    22.24|
 |MMLU-PRO (5-shot)  |    47.79|

 |MuSR (0-shot)      |    22.24|
 |MMLU-PRO (5-shot)  |    47.79|
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/prithivMLmods__Calcium-Opus-14B-Elite2-details)!
+Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=prithivMLmods%2FCalcium-Opus-14B-Elite2&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
+|      Metric       |Value (%)|
+|-------------------|--------:|
+|**Average**        |    40.25|
+|IFEval (0-Shot)    |    61.76|
+|BBH (3-Shot)       |    46.81|
+|MATH Lvl 5 (4-Shot)|    46.90|
+|GPQA (0-shot)      |    16.00|
+|MuSR (0-shot)      |    22.24|
+|MMLU-PRO (5-shot)  |    47.79|