Instructions to use Undi95/ReMM-L2-13B-PIPPA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Undi95/ReMM-L2-13B-PIPPA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Undi95/ReMM-L2-13B-PIPPA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Undi95/ReMM-L2-13B-PIPPA") model = AutoModelForCausalLM.from_pretrained("Undi95/ReMM-L2-13B-PIPPA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Undi95/ReMM-L2-13B-PIPPA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Undi95/ReMM-L2-13B-PIPPA" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Undi95/ReMM-L2-13B-PIPPA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Undi95/ReMM-L2-13B-PIPPA
- SGLang
How to use Undi95/ReMM-L2-13B-PIPPA 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 "Undi95/ReMM-L2-13B-PIPPA" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Undi95/ReMM-L2-13B-PIPPA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Undi95/ReMM-L2-13B-PIPPA" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Undi95/ReMM-L2-13B-PIPPA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Undi95/ReMM-L2-13B-PIPPA with Docker Model Runner:
docker model run hf.co/Undi95/ReMM-L2-13B-PIPPA
Commit History
-
Adding Evaluation Results (#2)
- Adding Evaluation Results (e8f25961657a0985914a2a1c87451f0aef3f7618) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>ba8a379
-
Update README.md
c74d621 -
Update README.md (#1)
- Update README.md (4c74317c73b50e36877590f7f144e682fea2767d) Co-authored-by: dfadf <llama-anon@users.noreply.huggingface.co>c36996c
-
Update README.md
79e7111 -
Create README.md
7d63c05 -
Upload tokenizer.model
f5ad5a1 -
Upload tokenizer
9e007fd -
Upload LlamaForCausalLM
956e479 -
initial commit
6631cc0