Text Generation
Transformers
Safetensors
English
llama
conversational
Eval Results (legacy)
text-generation-inference
Instructions to use Nitral-AI/Poppy_Porpoise-1.0-L3-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nitral-AI/Poppy_Porpoise-1.0-L3-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Nitral-AI/Poppy_Porpoise-1.0-L3-8B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Nitral-AI/Poppy_Porpoise-1.0-L3-8B") model = AutoModelForCausalLM.from_pretrained("Nitral-AI/Poppy_Porpoise-1.0-L3-8B", 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]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Nitral-AI/Poppy_Porpoise-1.0-L3-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Nitral-AI/Poppy_Porpoise-1.0-L3-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nitral-AI/Poppy_Porpoise-1.0-L3-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Nitral-AI/Poppy_Porpoise-1.0-L3-8B
- SGLang
How to use Nitral-AI/Poppy_Porpoise-1.0-L3-8B 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 "Nitral-AI/Poppy_Porpoise-1.0-L3-8B" \ --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": "Nitral-AI/Poppy_Porpoise-1.0-L3-8B", "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 "Nitral-AI/Poppy_Porpoise-1.0-L3-8B" \ --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": "Nitral-AI/Poppy_Porpoise-1.0-L3-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Nitral-AI/Poppy_Porpoise-1.0-L3-8B with Docker Model Runner:
docker model run hf.co/Nitral-AI/Poppy_Porpoise-1.0-L3-8B
- "Poppy Porpoise" is a cutting-edge AI roleplay assistant based on the Llama 3 8B model, specializing in crafting unforgettable narrative experiences. With its advanced language capabilities, Poppy expertly immerses users in an interactive and engaging adventure, tailoring each adventure to their individual preferences.
- : Presets in repo folder.
- : Lewdiculus Imatrix GGUF's.
- : 5bpw Exl2.
- : 8bpw Exl2.
- If you want to use vision functionality: You must use the latest versions of Koboldcpp. And need to load the specified mmproj file: Llava MMProj.
- OpenLLM Leaderboard results.
"Poppy Porpoise" is a cutting-edge AI roleplay assistant based on the Llama 3 8B model, specializing in crafting unforgettable narrative experiences. With its advanced language capabilities, Poppy expertly immerses users in an interactive and engaging adventure, tailoring each adventure to their individual preferences.
: Presets in repo folder.
: Lewdiculus Imatrix GGUF's.
: 5bpw Exl2.
: 8bpw Exl2.
If you want to use vision functionality: You must use the latest versions of Koboldcpp. And need to load the specified mmproj file: Llava MMProj.
OpenLLM Leaderboard results.
| Metric | Value |
|---|---|
| Avg. | 69.24 |
| AI2 Reasoning Challenge (25-Shot) | 63.40 |
| HellaSwag (10-Shot) | 82.89 |
| MMLU (5-Shot) | 68.04 |
| TruthfulQA (0-shot) | 54.12 |
| Winogrande (5-shot) | 77.90 |
| GSM8k (5-shot) | 69.07 |
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Model tree for Nitral-AI/Poppy_Porpoise-1.0-L3-8B
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard63.400
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard82.890
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard68.040
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard54.120
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.900
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard69.070

