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
| """ | |
| AWS CLI Tool - Wrap `aws` CLI for S3, EC2, Lambda, IAM operations. | |
| Author: Hieu Louis (2026) | |
| """ | |
| from __future__ import annotations | |
| import os | |
| import shlex | |
| import subprocess | |
| from typing import Dict, Any, List, Optional | |
| from .base import Tool, ToolResult, ToolContext, ToolCategory, ToolSafety | |
| # Service được hỗ trợ // Supported AWS services | |
| AWS_SERVICES = { | |
| "s3", "ec2", "lambda", "iam", "sts", "dynamodb", | |
| "rds", "cloudformation", "ecs", "ecr", "sns", "sqs", | |
| "cloudwatch", "logs", "ssm", "secretsmanager", | |
| } | |
| # Read-only ops (không cần confirmation) | |
| READONLY_OPS = {"ls", "get", "describe", "list", "cat", "head", "whoami", "get-caller-identity"} | |
| # Write ops (cần confirmation + dry_run) | |
| WRITE_OPS = {"cp", "mv", "rm", "sync", "create", "delete", "put", "update", "invoke", "run"} | |
| class AWSCliTool(Tool): | |
| """Wrap `aws` CLI cho S3/EC2/Lambda/IAM và các AWS service khác.""" | |
| category = ToolCategory.CLOUD | |
| safety = ToolSafety.DANGEROUS | |
| requires_confirmation = True | |
| def name(self) -> str: | |
| return "aws_cli" | |
| def description(self) -> str: | |
| return ( | |
| "Wrap aws CLI: S3 (ls/cp/rm/sync), EC2 (describe-instances, start/stop), " | |
| "Lambda (invoke/list), IAM, STS, và các service khác. Hỗ trợ --profile, --region, dry_run." | |
| ) | |
| def parameters(self) -> Dict[str, Any]: | |
| return { | |
| "type": "object", | |
| "properties": { | |
| "service": { | |
| "type": "string", | |
| "enum": sorted(AWS_SERVICES), | |
| "description": "AWS service name (s3, ec2, lambda, ...)", | |
| }, | |
| "operation": {"type": "string", "description": "CLI operation e.g. ls, cp, describe-instances"}, | |
| "args": { | |
| "type": "array", | |
| "items": {"type": "string"}, | |
| "description": "Positional args (bucket/key, instance-ids, ...)", | |
| }, | |
| "options": { | |
| "type": "object", | |
| "description": "--key value pairs", | |
| }, | |
| "profile": {"type": "string", "description": "AWS profile (--profile)"}, | |
| "region": {"type": "string", "description": "AWS region (--region)"}, | |
| "output_format": { | |
| "type": "string", | |
| "enum": ["json", "yaml", "text", "table"], | |
| "default": "json", | |
| }, | |
| }, | |
| "required": ["service", "operation"], | |
| } | |
| def validate_args(self, args: Dict[str, Any]) -> Optional[str]: | |
| svc = args.get("service") | |
| op = args.get("operation") | |
| if not svc: | |
| return "Missing required arg: service" | |
| if not op: | |
| return "Missing required arg: operation" | |
| if svc not in AWS_SERVICES: | |
| return f"Unsupported service: {svc}. Supported: {sorted(AWS_SERVICES)}" | |
| return None | |
| def _is_write_op(self, op: str) -> bool: | |
| op_lower = op.lower() | |
| for w in WRITE_OPS: | |
| if w in op_lower: | |
| return True | |
| return False | |
| def _build_command(self, args: Dict[str, Any]) -> List[str]: | |
| cmd: List[str] = ["aws"] | |
| if args.get("profile"): | |
| cmd += ["--profile", args["profile"]] | |
| if args.get("region"): | |
| cmd += ["--region", args["region"]] | |
| cmd += ["--output", args.get("output_format", "json")] | |
| cmd += [args["service"], args["operation"]] | |
| # Positional args | |
| for a in (args.get("args") or []): | |
| cmd.append(str(a)) | |
| # --key value options | |
| for k, v in (args.get("options") or {}).items(): | |
| if isinstance(v, bool): | |
| if v: | |
| cmd.append(f"--{k}") | |
| elif isinstance(v, (list, tuple)): | |
| for item in v: | |
| cmd += [f"--{k}", str(item)] | |
| else: | |
| cmd += [f"--{k}", str(v)] | |
| return cmd | |
| def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult: | |
| cmd = self._build_command(args) | |
| op = args["operation"] | |
| is_write = self._is_write_op(op) | |
| # Dry-run simulation | |
| if context.dry_run and is_write: | |
| return ToolResult( | |
| success=True, | |
| output=f"[dry-run] Would execute: {' '.join(cmd)}", | |
| metadata={ | |
| "dry_run": True, | |
| "command": cmd, | |
| "service": args["service"], | |
| "operation": op, | |
| }, | |
| ) | |
| env = dict(os.environ) | |
| env.update(context.env) | |
| try: | |
| result = subprocess.run( | |
| cmd, | |
| capture_output=True, | |
| text=True, | |
| env=env, | |
| timeout=context.timeout, | |
| check=False, | |
| ) | |
| return ToolResult( | |
| success=(result.returncode == 0), | |
| output=result.stdout, | |
| error=result.stderr or None, | |
| return_code=result.returncode, | |
| metadata={ | |
| "service": args["service"], | |
| "operation": op, | |
| "command": cmd, | |
| "profile": args.get("profile"), | |
| "region": args.get("region"), | |
| "dry_run": False, | |
| }, | |
| ) | |
| except FileNotFoundError: | |
| return ToolResult( | |
| success=False, | |
| error="aws CLI not found. Cài đặt AWS CLI v2.", | |
| return_code=127, | |
| ) | |
| except subprocess.TimeoutExpired: | |
| return ToolResult( | |
| success=False, | |
| error=f"aws command timed out after {context.timeout}s", | |
| return_code=124, | |
| ) | |
| except Exception as e: | |
| return ToolResult(success=False, error=str(e), return_code=1) | |