Text Generation
Transformers
Safetensors
qwen2
coder
code
agent
conversational
text-generation-inference
Instructions to use AdminReal/NexusCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdminReal/NexusCoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AdminReal/NexusCoder") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AdminReal/NexusCoder") model = AutoModelForCausalLM.from_pretrained("AdminReal/NexusCoder", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AdminReal/NexusCoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AdminReal/NexusCoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AdminReal/NexusCoder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AdminReal/NexusCoder
- SGLang
How to use AdminReal/NexusCoder 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 "AdminReal/NexusCoder" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AdminReal/NexusCoder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "AdminReal/NexusCoder" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AdminReal/NexusCoder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use AdminReal/NexusCoder with Docker Model Runner:
docker model run hf.co/AdminReal/NexusCoder
File size: 5,842 Bytes
eca5751 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 | """
Code Compiler Tool - Compile C/C++/Rust/Go source code.
Author: Hieu Louis (2026)
Wraps:
- C : gcc (gcc -o <out> <src> [-O2])
- C++ : g++ (g++ -o <out> <src> [-O2])
- Rust: rustc (rustc -O -o <out> <src>)
- Go : go build (go build -o <out> <src>)
Subprocess có timeout, capture stdout+stderr. Trả về binary path trong artifacts.
DANGEROUS (executes compiler), requires_confirmation.
"""
from __future__ import annotations
import os
import shlex
import shutil
import subprocess
from typing import Any, Dict, List, Optional
from .base import Tool, ToolResult, ToolContext, ToolCategory, ToolSafety
# Map language → (cmd, ext, optional subcommand)
COMPILERS: Dict[str, Dict[str, Any]] = {
"c": {"cmd": "gcc", "ext": ".c", "subcmd": None},
"cpp": {"cmd": "g++", "ext": ".cpp", "subcmd": None},
"rust": {"cmd": "rustc", "ext": ".rs", "subcmd": None},
"go": {"cmd": "go", "ext": ".go", "subcmd": "build"},
}
class CodeCompilerTool(Tool):
"""Compile C/C++/Rust/Go source code."""
category = ToolCategory.EXEC
safety = ToolSafety.DANGEROUS
requires_confirmation = True
@property
def name(self) -> str:
return "code_compiler"
@property
def description(self) -> str:
return (
"Compile C/C++/Rust/Go source code. Wraps gcc, g++, rustc, go build. "
"Hỗ trợ optimize flag (-O2 cho C/C++, -O cho Rust). "
"Trả về binary path trong artifacts."
)
@property
def parameters(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {"type": "string", "description": "Source file để compile"},
"language": {
"type": "string",
"enum": sorted(COMPILERS.keys()),
"description": "Ngôn ngữ",
},
"output": {
"type": "string",
"description": "Binary output path (default: <source>.out)",
},
"optimize": {"type": "boolean", "description": "Enable -O2/-O (default false)"},
"extra_args": {
"type": "array",
"items": {"type": "string"},
"description": "Compiler flags bổ sung",
},
},
"required": ["path", "language"],
}
def validate_args(self, args: Dict[str, Any]) -> Optional[str]:
if not args.get("path"):
return "Missing required arg: path"
lang = args.get("language")
if not lang:
return "Missing required arg: language"
if lang not in COMPILERS:
return f"Unsupported language: {lang}. Chọn: {sorted(COMPILERS.keys())}"
return None
def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult:
path: str = args["path"]
lang: str = args["language"]
optimize: bool = bool(args.get("optimize", False))
extra_args: List[str] = list(args.get("extra_args", []))
if not os.path.isfile(path):
return ToolResult(success=False, error=f"Source file không tồn tại: {path}", return_code=1)
spec = COMPILERS[lang]
cmd: str = spec["cmd"]
if not shutil.which(cmd):
return ToolResult(
success=False,
error=f"Compiler '{cmd}' không tìm thấy. Cài đặt để compile {lang}.",
return_code=127,
metadata={"language": lang, "missing": cmd},
)
# Output binary path (default next to source)
out_path: str = args.get("output") or os.path.splitext(path)[0] + ".out"
# Build command
full_cmd: List[str] = [cmd]
if spec.get("subcmd"):
full_cmd.append(spec["subcmd"])
if optimize and lang in ("c", "cpp"):
full_cmd.append("-O2")
if optimize and lang == "rust":
full_cmd.append("-O")
full_cmd += ["-o", out_path, path]
full_cmd += extra_args
if context.dry_run:
return ToolResult(
success=True,
output=f"[dry-run] Sẽ compile: {' '.join(shlex.quote(c) for c in full_cmd)}",
metadata={
"language": lang,
"command": full_cmd,
"output": out_path,
"optimize": optimize,
"dry_run": True,
},
)
try:
cp = subprocess.run(
full_cmd,
capture_output=True,
text=True,
timeout=context.timeout,
cwd=context.working_dir,
env={**os.environ, **context.env},
)
except subprocess.TimeoutExpired:
return ToolResult(
success=False,
error=f"Compile timeout ({context.timeout}s)",
return_code=124,
metadata={"language": lang, "command": " ".join(full_cmd)},
)
except FileNotFoundError:
return ToolResult(success=False, error=f"{cmd} not found", return_code=127)
artifacts: List[str] = []
if cp.returncode == 0 and os.path.isfile(out_path):
artifacts.append(out_path)
return ToolResult(
success=(cp.returncode == 0),
output=cp.stdout,
error=cp.stderr if cp.stderr else None,
return_code=cp.returncode,
artifacts=artifacts,
metadata={
"language": lang,
"command": " ".join(full_cmd),
"output": out_path,
"optimize": optimize,
},
)
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