Text Generation
Transformers
PyTorch
English
gpt_bigcode
Eval Results (legacy)
text-generation-inference
Instructions to use abacaj/starcoderbase-1b-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abacaj/starcoderbase-1b-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="abacaj/starcoderbase-1b-sft")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("abacaj/starcoderbase-1b-sft") model = AutoModelForCausalLM.from_pretrained("abacaj/starcoderbase-1b-sft") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use abacaj/starcoderbase-1b-sft with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "abacaj/starcoderbase-1b-sft" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "abacaj/starcoderbase-1b-sft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/abacaj/starcoderbase-1b-sft
- SGLang
How to use abacaj/starcoderbase-1b-sft 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 "abacaj/starcoderbase-1b-sft" \ --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": "abacaj/starcoderbase-1b-sft", "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 "abacaj/starcoderbase-1b-sft" \ --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": "abacaj/starcoderbase-1b-sft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use abacaj/starcoderbase-1b-sft with Docker Model Runner:
docker model run hf.co/abacaj/starcoderbase-1b-sft
QGML with Starcoder.cpp only needs less than 3GB GPU
#4
by DevElCuy - opened
First of all thanks for this great model!
I managed to convert it to GGML with https://github.com/bigcode-project/starcoder.cpp
And this is how I load it:
from ctransformers import (
AutoModelForCausalLM,
AutoTokenizer
)
from transformers import pipeline
from langchain.llms import HuggingFacePipeline
model_name = "models/abacaj--starcoderbase-1b-sft-ggml.bin"
model = AutoModelForCausalLM.from_pretrained(
model_name,
model_type="gpt_bigcode",
gpu_layers=1024,
hf=True
)
tokenizer = AutoTokenizer.from_pretrained(model)
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
max_length=2048,
)
llm = HuggingFacePipeline(
pipeline=pipe,
)
Dependencies (requirements.txt):
torch==2.0.1
transformers==4.33.1
langchain==0.0.285
ctransformers==0.2.26