Instructions to use appvoid/palmer-002-32k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use appvoid/palmer-002-32k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="appvoid/palmer-002-32k")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("appvoid/palmer-002-32k") model = AutoModelForCausalLM.from_pretrained("appvoid/palmer-002-32k") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use appvoid/palmer-002-32k with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "appvoid/palmer-002-32k" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "appvoid/palmer-002-32k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/appvoid/palmer-002-32k
- SGLang
How to use appvoid/palmer-002-32k 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 "appvoid/palmer-002-32k" \ --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": "appvoid/palmer-002-32k", "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 "appvoid/palmer-002-32k" \ --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": "appvoid/palmer-002-32k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use appvoid/palmer-002-32k with Docker Model Runner:
docker model run hf.co/appvoid/palmer-002-32k
palmer
a better base model
This model is palmer-002-2401 scaled to 32k by merging and fine-tuning with TinyLlama-1.1B-32k-Instruct by Doctor-Shotgun
evaluation π§ͺ
note that this is a zero-shot setting as opposite to open llm leaderboard's few-shot evals
model ARC-C OBQA HellaSwag PIQA Winogrande Average
tinyllama | 0.3029 | 0.3600 | 0.5935 | 0.7329 | 0.5959 | 0.5170 |
palmer-002-2401 | 0.3294 | 0.3700 | 0.5950 | 0.7399 | 0.5896 | 0.5247 |
palmer-002-32k | 0.3268 | 0.3780 | 0.5785 | 0.7492 | 0.6251 | 0.5315 | (this)
babbage-002 | 0.3285 | 0.3620 | 0.6380 | 0.7606 | 0.6085 | 0.5395 |
This model's performance is close to openai's one while being capable of using 2x the context size.
prompt π
no prompt π
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