Instructions to use caikybaldo999/webcoder-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use caikybaldo999/webcoder-pro with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="caikybaldo999/webcoder-pro")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("caikybaldo999/webcoder-pro")
model = AutoModelForCausalLM.from_pretrained("caikybaldo999/webcoder-pro", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use caikybaldo999/webcoder-pro with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "caikybaldo999/webcoder-pro"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "caikybaldo999/webcoder-pro",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/caikybaldo999/webcoder-pro

SGLang

How to use caikybaldo999/webcoder-pro 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 "caikybaldo999/webcoder-pro" \
    --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": "caikybaldo999/webcoder-pro",
		"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 "caikybaldo999/webcoder-pro" \
        --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": "caikybaldo999/webcoder-pro",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use caikybaldo999/webcoder-pro with Docker Model Runner:
```
docker model run hf.co/caikybaldo999/webcoder-pro
```

webcoder-pro

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{
  "model_name": "webcoder-100m",
  "output_dir": "/content/webcoder-100m",
  "tokenizer_dir": "/content/webcoder-tokenizer",
  "seed": 42,
  "dataset_id": "bigcode/the-stack-smol-xl",
  "languages": [
    "html",
    "css",
    "javascript"
  ],
  "max_samples_per_language": 10000,
  "min_chars": 120,
  "max_chars": 20000,
  "license_filter": true,
  "vocab_size": 27664,
  "context_length": 1024,
  "n_embd": 768,
  "n_layer": 11,
  "n_head": 12,
  "train_batch_size": 8,
  "eval_batch_size": 8,
  "gradient_accumulation_steps": 4,
  "learning_rate": 0.0004,
  "weight_decay": 0.1,
  "warmup_ratio": 0.03,
  "max_steps": 8000,
  "time_limit_minutes": 55,
  "logging_steps": 20,
  "eval_steps": 250,
  "save_steps": 500,
  "save_total_limit": 3,
  "hf_repo_id": "caikybaldo999/webcoder-pro",
  "hf_private": false
}