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)# pip install -U transformers accelerate # 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=256) 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: 8,673 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 | """File Operations Tools - read/write/list/delete files."""
from __future__ import annotations
import os
import glob
from typing import Dict, Any, List
from pathlib import Path
from .base import Tool, ToolResult, ToolContext, ToolCategory, ToolSafety
class FileReadTool(Tool):
"""Đọc nội dung file."""
category = ToolCategory.FILE
safety = ToolSafety.SAFE
@property
def name(self) -> str:
return "file_read"
@property
def description(self) -> str:
return "Đọc nội dung file text. Hỗ trợ offset/limit cho file lớn."
@property
def parameters(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {"type": "string", "description": "Đường dẫn file"},
"offset": {"type": "integer", "description": "Dòng bắt đầu (0-indexed)", "default": 0},
"limit": {"type": "integer", "description": "Số dòng tối đa", "default": 2000},
"encoding": {"type": "string", "default": "utf-8"},
},
"required": ["path"],
}
def validate_args(self, args: Dict[str, Any]) -> Any:
path = args.get("path")
if not path:
return "Missing required arg: path"
full_path = os.path.join(os.getcwd(), path) if not os.path.isabs(path) else path
if not os.path.exists(full_path):
return f"File not found: {path}"
return None
def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult:
path = args["path"]
offset = args.get("offset", 0)
limit = args.get("limit", 2000)
encoding = args.get("encoding", "utf-8")
full_path = path if os.path.isabs(path) else os.path.join(context.working_dir, path)
try:
with open(full_path, "r", encoding=encoding) as f:
lines = f.readlines()
total_lines = len(lines)
selected = lines[offset:offset + limit]
content = "".join(selected)
return ToolResult(
success=True,
output=content,
metadata={
"path": full_path,
"total_lines": total_lines,
"shown_lines": len(selected),
"offset": offset,
},
)
except Exception as e:
return ToolResult(success=False, error=str(e), return_code=1)
class FileWriteTool(Tool):
"""Ghi nội dung vào file (overwrite hoặc append)."""
category = ToolCategory.FILE
safety = ToolSafety.MODERATE
requires_confirmation = True
@property
def name(self) -> str:
return "file_write"
@property
def description(self) -> str:
return "Ghi content vào file. Hỗ trợ append mode."
@property
def parameters(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {"type": "string"},
"content": {"type": "string"},
"append": {"type": "boolean", "default": False},
"create_dirs": {"type": "boolean", "default": True},
"encoding": {"type": "string", "default": "utf-8"},
},
"required": ["path", "content"],
}
def validate_args(self, args: Dict[str, Any]) -> Any:
if not args.get("path"):
return "Missing required arg: path"
if "content" not in args:
return "Missing required arg: content"
return None
def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult:
path = args["path"]
content = args["content"]
append = args.get("append", False)
create_dirs = args.get("create_dirs", True)
encoding = args.get("encoding", "utf-8")
full_path = path if os.path.isabs(path) else os.path.join(context.working_dir, path)
try:
if create_dirs:
os.makedirs(os.path.dirname(full_path) or ".", exist_ok=True)
mode = "a" if append else "w"
with open(full_path, mode, encoding=encoding) as f:
f.write(content)
return ToolResult(
success=True,
output=f"Wrote {len(content)} chars to {full_path}",
artifacts=[full_path],
metadata={"bytes": len(content.encode(encoding)), "append": append},
)
except Exception as e:
return ToolResult(success=False, error=str(e), return_code=1)
class FileListTool(Tool):
"""Liệt kê files trong thư mục."""
category = ToolCategory.FILE
safety = ToolSafety.SAFE
@property
def name(self) -> str:
return "file_list"
@property
def description(self) -> str:
return "Liệt kê files trong thư mục với glob pattern."
@property
def parameters(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {"type": "string", "default": "."},
"pattern": {"type": "string", "default": "*"},
"recursive": {"type": "boolean", "default": False},
"include_hidden": {"type": "boolean", "default": False},
},
}
def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult:
path = args.get("path", ".")
pattern = args.get("pattern", "*")
recursive = args.get("recursive", False)
include_hidden = args.get("include_hidden", False)
full_path = path if os.path.isabs(path) else os.path.join(context.working_dir, path)
if recursive:
glob_pattern = os.path.join(full_path, "**", pattern)
files = glob.glob(glob_pattern, recursive=True)
else:
glob_pattern = os.path.join(full_path, pattern)
files = glob.glob(glob_pattern)
if not include_hidden:
files = [f for f in files if not os.path.basename(f).startswith(".")]
files_sorted = sorted(files)
output_lines = []
for f in files_sorted:
try:
if os.path.isdir(f):
output_lines.append(f" 📁 {f}/")
else:
size = os.path.getsize(f)
output_lines.append(f" 📄 {f} ({size} bytes)")
except OSError:
output_lines.append(f" ❓ {f}")
return ToolResult(
success=True,
output="\n".join(output_lines) or "(empty)",
metadata={"count": len(files_sorted), "path": full_path},
)
class FileDeleteTool(Tool):
"""Xóa file hoặc thư mục."""
category = ToolCategory.FILE
safety = ToolSafety.DESTRUCTIVE
requires_confirmation = True
@property
def name(self) -> str:
return "file_delete"
@property
def description(self) -> str:
return "Xóa file hoặc thư mục. CẢNH BÁO: không thể undo!"
@property
def parameters(self) -> Dict[str, Any]:
return {
"type": "object",
"properties": {
"path": {"type": "string"},
"recursive": {"type": "boolean", "default": False},
},
"required": ["path"],
}
def execute(self, args: Dict[str, Any], context: ToolContext) -> ToolResult:
import shutil
path = args["path"]
recursive = args.get("recursive", False)
full_path = path if os.path.isabs(path) else os.path.join(context.working_dir, path)
if not os.path.exists(full_path):
return ToolResult(success=False, error=f"Not found: {full_path}", return_code=1)
try:
if os.path.isdir(full_path):
if not recursive:
return ToolResult(
success=False,
error="Is a directory. Use recursive=True to delete.",
return_code=1,
)
shutil.rmtree(full_path)
else:
os.remove(full_path)
return ToolResult(
success=True,
output=f"Deleted: {full_path}",
metadata={"deleted_path": full_path},
)
except Exception as e:
return ToolResult(success=False, error=str(e), return_code=1)
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