Text Generation
Transformers
PyTorch
Safetensors
code
gpt_bigcode
Eval Results (legacy)
text-generation-inference
Instructions to use bigcode/gpt_bigcode-santacoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigcode/gpt_bigcode-santacoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bigcode/gpt_bigcode-santacoder")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bigcode/gpt_bigcode-santacoder") model = AutoModelForCausalLM.from_pretrained("bigcode/gpt_bigcode-santacoder") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use bigcode/gpt_bigcode-santacoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bigcode/gpt_bigcode-santacoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bigcode/gpt_bigcode-santacoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bigcode/gpt_bigcode-santacoder
- SGLang
How to use bigcode/gpt_bigcode-santacoder 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 "bigcode/gpt_bigcode-santacoder" \ --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": "bigcode/gpt_bigcode-santacoder", "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 "bigcode/gpt_bigcode-santacoder" \ --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": "bigcode/gpt_bigcode-santacoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bigcode/gpt_bigcode-santacoder with Docker Model Runner:
docker model run hf.co/bigcode/gpt_bigcode-santacoder
Commit ·
97c7c17
1
Parent(s): c72ef96
Update config for hf transformers
Browse files- config.json +3 -5
config.json
CHANGED
|
@@ -1,15 +1,14 @@
|
|
| 1 |
{
|
| 2 |
"activation_function": "gelu_pytorch_tanh",
|
| 3 |
"architectures": [
|
| 4 |
-
"
|
| 5 |
],
|
| 6 |
"attention_softmax_in_fp32": true,
|
| 7 |
-
"
|
| 8 |
"attn_pdrop": 0.1,
|
| 9 |
"bos_token_id": 50256,
|
| 10 |
"embd_pdrop": 0.1,
|
| 11 |
"eos_token_id": 50256,
|
| 12 |
-
"inference_runner": 0,
|
| 13 |
"initializer_range": 0.02,
|
| 14 |
"layer_norm_epsilon": 1e-05,
|
| 15 |
"model_type": "gpt_bigcode",
|
|
@@ -27,8 +26,7 @@
|
|
| 27 |
"summary_proj_to_labels": true,
|
| 28 |
"summary_type": "cls_index",
|
| 29 |
"summary_use_proj": true,
|
| 30 |
-
"transformers_version": "4.
|
| 31 |
"use_cache": true,
|
| 32 |
-
"validate_runner_input": true,
|
| 33 |
"vocab_size": 49280
|
| 34 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"activation_function": "gelu_pytorch_tanh",
|
| 3 |
"architectures": [
|
| 4 |
+
"GPTBigCodeForCausalLM"
|
| 5 |
],
|
| 6 |
"attention_softmax_in_fp32": true,
|
| 7 |
+
"multi_query": true,
|
| 8 |
"attn_pdrop": 0.1,
|
| 9 |
"bos_token_id": 50256,
|
| 10 |
"embd_pdrop": 0.1,
|
| 11 |
"eos_token_id": 50256,
|
|
|
|
| 12 |
"initializer_range": 0.02,
|
| 13 |
"layer_norm_epsilon": 1e-05,
|
| 14 |
"model_type": "gpt_bigcode",
|
|
|
|
| 26 |
"summary_proj_to_labels": true,
|
| 27 |
"summary_type": "cls_index",
|
| 28 |
"summary_use_proj": true,
|
| 29 |
+
"transformers_version": "4.28.0.dev0",
|
| 30 |
"use_cache": true,
|
|
|
|
| 31 |
"vocab_size": 49280
|
| 32 |
}
|