Text Generation
Transformers
Safetensors
English
gptx2
language-model
transformer
rope
swiglu
xgqa
custom-architecture
custom-tokenizer
curriculum-learning
code-normalization
tx-3
custom_code
Instructions to use AxiomicLabs/GPT-X2.5-135M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AxiomicLabs/GPT-X2.5-135M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AxiomicLabs/GPT-X2.5-135M", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("AxiomicLabs/GPT-X2.5-135M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AxiomicLabs/GPT-X2.5-135M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AxiomicLabs/GPT-X2.5-135M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AxiomicLabs/GPT-X2.5-135M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AxiomicLabs/GPT-X2.5-135M
- SGLang
How to use AxiomicLabs/GPT-X2.5-135M 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 "AxiomicLabs/GPT-X2.5-135M" \ --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": "AxiomicLabs/GPT-X2.5-135M", "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 "AxiomicLabs/GPT-X2.5-135M" \ --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": "AxiomicLabs/GPT-X2.5-135M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AxiomicLabs/GPT-X2.5-135M with Docker Model Runner:
docker model run hf.co/AxiomicLabs/GPT-X2.5-135M
Man Delivers
#2
by GODELEV - opened
@Datdanboi25 , You always Delivers Sota models , Setting up the benchmark for the community
I think soon you will beat Smollm2-135M ,
800 hours Man!!
Ty man!
Hyped for ur next model!
Well , You should be hyperd for rose 1.5 series , its performing far better
GODELEV changed discussion status to closed