Instructions to use Tijmen2/cosmosage-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Tijmen2/cosmosage-v3 with Transformers:

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

pipe = pipeline("text-generation", model="Tijmen2/cosmosage-v3")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Tijmen2/cosmosage-v3")
model = AutoModelForCausalLM.from_pretrained("Tijmen2/cosmosage-v3", device_map="auto")
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]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Tijmen2/cosmosage-v3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Tijmen2/cosmosage-v3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tijmen2/cosmosage-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Tijmen2/cosmosage-v3

SGLang

How to use Tijmen2/cosmosage-v3 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 "Tijmen2/cosmosage-v3" \
    --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": "Tijmen2/cosmosage-v3",
		"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 "Tijmen2/cosmosage-v3" \
        --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": "Tijmen2/cosmosage-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Tijmen2/cosmosage-v3 with Docker Model Runner:
```
docker model run hf.co/Tijmen2/cosmosage-v3
```

Tijmen2

leaderboard-pr-bot commited on Sep 3, 2024

Commit

a53eeb4

verified ·

1 Parent(s): e6d4b4e

Adding Evaluation Results (#2)

Browse files

- Adding Evaluation Results (4d27eab767fdd734aaf21146c43e63e8c05c16d4)

Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +21 -8

README.md CHANGED Viewed

@@ -1,17 +1,17 @@
 ---
 tags:
 - physics
 - cosmology
-model-index:
-- name: cosmosage-v3
-  results: []
-license: mit
-language:
-- en
-pipeline_tag: text-generation
 base_model: meta-llama/Meta-Llama-3-8B
 datasets:
 - teknium/OpenHermes-2.5
 ---
 # cosmosage
@@ -97,4 +97,17 @@ cosmosage can be cited using the following BibTeX entry:
 }
 ```
-[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)

 ---
+language:
+- en
+license: mit
 tags:
 - physics
 - cosmology
 base_model: meta-llama/Meta-Llama-3-8B
 datasets:
 - teknium/OpenHermes-2.5
+pipeline_tag: text-generation
+model-index:
+- name: cosmosage-v3
+  results: []
 ---
 # cosmosage
 }
 ```
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+# [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/details_Tijmen2__cosmosage-v3)
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |16.80|
+|IFEval (0-Shot)    |44.82|
+|BBH (3-Shot)       |22.69|
+|MATH Lvl 5 (4-Shot)| 1.74|
+|GPQA (0-shot)      | 4.36|
+|MuSR (0-shot)      |10.69|
+|MMLU-PRO (5-shot)  |16.51|