Instructions to use TehVenom/Pygmalion-13b-Merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TehVenom/Pygmalion-13b-Merged with Transformers:

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

pipe = pipeline("text-generation", model="TehVenom/Pygmalion-13b-Merged")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TehVenom/Pygmalion-13b-Merged")
model = AutoModelForCausalLM.from_pretrained("TehVenom/Pygmalion-13b-Merged")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TehVenom/Pygmalion-13b-Merged with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TehVenom/Pygmalion-13b-Merged"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TehVenom/Pygmalion-13b-Merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TehVenom/Pygmalion-13b-Merged

SGLang

How to use TehVenom/Pygmalion-13b-Merged 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 "TehVenom/Pygmalion-13b-Merged" \
    --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": "TehVenom/Pygmalion-13b-Merged",
		"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 "TehVenom/Pygmalion-13b-Merged" \
        --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": "TehVenom/Pygmalion-13b-Merged",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TehVenom/Pygmalion-13b-Merged with Docker Model Runner:
```
docker model run hf.co/TehVenom/Pygmalion-13b-Merged
```

leaderboard-pr-bot commited on Nov 17, 2023

Commit

9893031

1 Parent(s): f963080

Adding Evaluation Results

Browse files

This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr

The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.

If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions

Files changed (1) hide show

README.md +14 -0

README.md CHANGED Viewed

@@ -117,3 +117,17 @@ Current evals out of the Pygmalion-13b model: <br>
 The intended use-case for this model is fictional conversation for entertainment purposes. Any other sort of usage is out of scope.
 As such, it was **not** fine-tuned to be safe and harmless: the base model _and_ this fine-tune have been trained on data known to contain profanity and texts that are lewd or otherwise offensive. It may produce socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive. Outputs might often be factually wrong or misleading.

 The intended use-case for this model is fictional conversation for entertainment purposes. Any other sort of usage is out of scope.
 As such, it was **not** fine-tuned to be safe and harmless: the base model _and_ this fine-tune have been trained on data known to contain profanity and texts that are lewd or otherwise offensive. It may produce socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive. Outputs might often be factually wrong or misleading.
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_TehVenom__Pygmalion-13b-Merged)
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 44.8   |
+| ARC (25-shot)         | 56.48          |
+| HellaSwag (10-shot)   | 80.02    |
+| MMLU (5-shot)         | 42.93         |
+| TruthfulQA (0-shot)   | 35.86   |
+| Winogrande (5-shot)   | 75.53   |
+| GSM8K (5-shot)        | 0.08        |
+| DROP (3-shot)         | 22.67         |