Text Generation
Transformers
Safetensors
English
starcoder2
code
starcoder
bigcode
sft
7b
text-generation-inference
Instructions to use abideen/starcoder2-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abideen/starcoder2-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="abideen/starcoder2-chat")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("abideen/starcoder2-chat") model = AutoModelForCausalLM.from_pretrained("abideen/starcoder2-chat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use abideen/starcoder2-chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "abideen/starcoder2-chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "abideen/starcoder2-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/abideen/starcoder2-chat
- SGLang
How to use abideen/starcoder2-chat 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 "abideen/starcoder2-chat" \ --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": "abideen/starcoder2-chat", "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 "abideen/starcoder2-chat" \ --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": "abideen/starcoder2-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use abideen/starcoder2-chat with Docker Model Runner:
docker model run hf.co/abideen/starcoder2-chat
metadata
license: cc-by-nc-4.0
base_model: bigcode/starcoder2-7b
language:
- en
library_name: transformers
pipeline_tag: text-generation
tags:
- code
- starcoder
- bigcode
- sft
- 7b
Starcoder-2-chat
Starcoder-2-chat is an instruction fine-tuned of bigcode/starcoder2-7b using the glaiveai/glaive-code-assistant-v2 dataset using LoRA.
๐ Evaluation results
Thanks to Muhammad Bin Usman for running evals on Starcoder2-chat.
HUMANEVAL
0.3231707317073171
HUMANEVALPLUS
0.25609756097560976
INSTRUCT-HUMANEVAL
0.3231707317073171
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-7
- train_batch_size: 2
- eval_batch_size: Not specified
- seed: Not specified
- gradient_accumulation_steps: 8
- total_train_batch_size: Not specified
- optimizer: PagedAdamW with 32-bit precision
- lr_scheduler_type: Cosine
- lr_scheduler_warmup_steps: 100
- training_epoch: 1
Framework versions
- Transformers 4.39.0.dev0
- Peft 0.9.1.dev0
- Datasets 2.18.0
- torch 2.2.0
- accelerate 0.27.2
