Instructions to use caikybaldo999/webcoder-100m-html-css-js with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use caikybaldo999/webcoder-100m-html-css-js with Transformers:

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

pipe = pipeline("text-generation", model="caikybaldo999/webcoder-100m-html-css-js")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("caikybaldo999/webcoder-100m-html-css-js")
model = AutoModelForCausalLM.from_pretrained("caikybaldo999/webcoder-100m-html-css-js", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use caikybaldo999/webcoder-100m-html-css-js with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "caikybaldo999/webcoder-100m-html-css-js"
# 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-100m-html-css-js",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/caikybaldo999/webcoder-100m-html-css-js

SGLang

How to use caikybaldo999/webcoder-100m-html-css-js 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-100m-html-css-js" \
    --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-100m-html-css-js",
		"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-100m-html-css-js" \
        --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-100m-html-css-js",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use caikybaldo999/webcoder-100m-html-css-js with Docker Model Runner:
```
docker model run hf.co/caikybaldo999/webcoder-100m-html-css-js
```

webcoder-100m-html-css-js / training_config.json

caikybaldo999

Upload folder using huggingface_hub

ee9c8c2 verified about 16 hours ago

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	{
	"model_name": "WebCoder-100M",
	"vocab_size": 28672,
	"hidden_size": 768,
	"intermediate_size": 2048,
	"num_hidden_layers": 11,
	"num_attention_heads": 12,
	"num_key_value_heads": 12,
	"max_position_embeddings": 2048,
	"seq_len": 1024,
	"docs_per_language": 10000,
	"tokenizer_docs_per_language": 4000,
	"max_chars_per_doc": 200000,
	"micro_batch_size": 8,
	"grad_accum_steps": 4,
	"pretrain_lr": 0.0003,
	"sft_lr": 8e-05,
	"weight_decay": 0.1,
	"grad_clip": 1.0,
	"max_total_tokens": 2000000000,
	"pretrain_token_cap": 1950000000,
	"sft_token_cap": 50000000,
	"pretrain_warmup_tokens": 2000000,
	"pretrain_decay_tokens": 250000000,
	"sft_warmup_tokens": 250000,
	"sft_decay_tokens": 25000000,
	"train_minutes": 55.0,
	"reserve_sft_minutes": 10.0,
	"checkpoint_every_updates": 500,
	"log_every_updates": 20,
	"sft_dataset": "iamtarun/code_instructions_120k_alpaca",
	"sft_max_examples": 40000,
	"sft_epochs": 2,
	"work_dir": "/content/webcoder100m",
	"use_google_drive": false,
	"drive_dir": "/content/drive/MyDrive/WebCoder100M",
	"hf_repo_name": "webcoder-100m-html-css-js",
	"hf_private": false
	}