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
Download nexus/skills/code_translation.py from AdminReal/NexusCoder: direct link, hf CLI and curl.
- Browser
- Download file 10.8 kB
-
https://huggingface.co/AdminReal/NexusCoder/resolve/main/nexus/skills/code_translation.py
- Command line
-
hf download hf://AdminReal/NexusCoder/nexus/skills/code_translation.py
-
curl -L -o code_translation.py https://huggingface.co/AdminReal/NexusCoder/resolve/main/nexus/skills/code_translation.py
10.8 kB
| """Code Translation Skill - Dịch code giữa các ngôn ngữ lập trình. | |
| Hỗ trợ transpile Python <-> JS/TS, Go, Rust, Java, C++, C# với chiến lược | |
| mapping idioms, thư viện tương đương, và xử lý khác biệt type system. | |
| Author: Hieu Louis (2026) | |
| """ | |
| from __future__ import annotations | |
| from typing import Dict, List | |
| from .base import Skill, SkillContext, SkillCategory, SkillPriority, SkillResult | |
| class CodeTranslationSkill(Skill): | |
| """Dịch code từ ngôn ngữ này sang ngôn ngữ khác, giữ nguyên ngữ nghĩa.""" | |
| category = SkillCategory.CODE | |
| priority = SkillPriority.MEDIUM | |
| keywords: List[str] = [ | |
| "translate", "dịch", "convert", "chuyển", "transpile", | |
| "port", "porting", "python to", "python sang", | |
| "javascript to", "go to", "rust to", "java to", | |
| "to python", "to javascript", "to go", "to rust", | |
| "convert python", "migrate code", | |
| ] | |
| examples = [ | |
| "Convert Python script to Go", | |
| "Translate this JavaScript function to Rust", | |
| "Port Java code to Python idiomatic style", | |
| ] | |
| def name(self) -> str: | |
| return "code_translation" | |
| def description(self) -> str: | |
| return ( | |
| "Dịch code giữa các ngôn ngữ: Python, JS/TS, Go, Rust, Java, C++, C#. " | |
| "Transpile + idiomatic rewrite + thư viện tương đương." | |
| ) | |
| def can_handle(self, prompt: str, context: SkillContext = None) -> float: | |
| prompt_lower = prompt.lower() | |
| score = 0.0 | |
| for kw in self.keywords: | |
| if kw in prompt_lower: | |
| score += 0.15 | |
| # Phát hiện cặp "X to Y" pattern / detect "X to Y" pattern | |
| langs = ("python", "javascript", "js", "typescript", "ts", "go", | |
| "rust", "java", "c++", "c#") | |
| for src in langs: | |
| for dst in langs: | |
| if src != dst and f"{src} to {dst}" in prompt_lower: | |
| score += 0.25 | |
| break | |
| return min(1.0, score) | |
| def execute(self, context: SkillContext) -> SkillResult: | |
| return SkillResult( | |
| success=True, | |
| output=( | |
| "[CodeTranslation] Transpilation strategy ready. " | |
| "Mapping idioms, library equivalents, and type system differences." | |
| ), | |
| artifacts=[ | |
| {"path": "translation/language_mapping.md", "content": _LANGUAGE_MAPPING}, | |
| {"path": "translation/transpile_strategy.py", "content": _TRANSPILE_STRATEGY}, | |
| ], | |
| metadata={ | |
| "skill": self.name, | |
| "supported_pairs": [ | |
| "python<->javascript", "python<->go", "python<->rust", | |
| "python<->java", "javascript<->typescript", | |
| "java<->c#", "c++<->rust", | |
| ], | |
| "translation_phases": [ | |
| "1. Lexical + syntactic parse (AST) của source", | |
| "2. Type inference nếu đích statically typed", | |
| "3. Idiom mapping (list comprehension -> for-loop, etc.)", | |
| "4. Library substitution (requests -> fetch/http, numpy -> ndarray)", | |
| "5. Error/exception model translation (try/except <-> Result/Option)", | |
| "6. Concurrency primitive mapping (asyncio <-> tokio <-> goroutines)", | |
| "7. Idiomatic rewrite + formatting (ruff / gofmt / rustfmt)", | |
| "8. Generate equivalence tests (golden file) để verify semantic", | |
| ], | |
| "idiom_examples": { | |
| "list_comprehension": "Python: [f(x) for x in xs] -> Rust: xs.iter().map(f).collect()", | |
| "dict_default": "Python: d.get(k, default) -> Go: if v, ok := d[k]; !ok { ... }", | |
| "optional_chaining": "JS: a?.b?.c -> Rust: a.and_then(|x| x.b).and_then(|y| y.c)", | |
| "decorator": "Python @cache -> Java @Cacheable annotation", | |
| "exception_to_result": "Python try/except -> Rust Result<T, E> + ? operator", | |
| "generator": "Python yield -> Go channel + goroutine", | |
| }, | |
| "library_equivalents": { | |
| "http_client": { | |
| "python": "httpx/requests", | |
| "js": "fetch/axios", | |
| "go": "net/http", | |
| "rust": "reqwest", | |
| }, | |
| "json": { | |
| "python": "json", | |
| "js": "JSON", | |
| "go": "encoding/json", | |
| "rust": "serde_json", | |
| }, | |
| "async": { | |
| "python": "asyncio", | |
| "js": "Promise/async-await", | |
| "go": "goroutines+channels", | |
| "rust": "tokio", | |
| }, | |
| "testing": { | |
| "python": "pytest", | |
| "js": "jest/vitest", | |
| "go": "testing", | |
| "rust": "cargo test", | |
| }, | |
| }, | |
| }, | |
| suggestions=[ | |
| "Provide source code in a fenced block để dịch chính xác", | |
| "Specify target language version (e.g. Python 3.12 vs 3.8)", | |
| "Indicate whether to keep exact behavior or rewrite idiomatically", | |
| "Run golden tests to verify semantic equivalence post-translation", | |
| ], | |
| ) | |
| _LANGUAGE_MAPPING = '''# Language Mapping Reference | |
| | Construct | Python | JavaScript | Go | Rust | | |
| |------------------|---------------------|---------------------|---------------------|---------------------| | |
| | Variable | x = 1 | let x = 1 | x := 1 | let x = 1 | | |
| | Constant | X = 1 (convention) | const x = 1 | const x = 1 | const X: i32 = 1 | | |
| | Function | def f(x): ... | function f(x){} | func f(x T){} | fn f(x: T) {} | | |
| | Lambda | lambda x: x+1 | x => x+1 | func(x T)T{return} | `\\|x\\| x+1` | | |
| | List/Array | [1,2,3] | [1,2,3] | []int{1,2,3} | vec![1,2,3] | | |
| | Dict/Map | {"a":1} | {a:1} | map[string]int | HashMap::new() | | |
| | Optional | x=None | x=undefined/null | *T + ok pattern | Option<T> | | |
| | Error | raise ValueError | throw new Error | return err | return Err(...) | | |
| | Class | class C: | class C {} | struct + methods | struct + impl | | |
| | Interface | (duck typing) | (structural) | interface | trait | | |
| | Generics | (runtime) | (TS only) | [T any] | <T> | | |
| | Async | async def / await | async/await | go func(){} | async fn / .await | | |
| ## Type System Differences | |
| | Concern | Python | JS/TS | Go | Rust | | |
| |--------------------|-----------------|------------------------|----------------------|---------------------| | |
| | Null safety | None checks | undefined/null | nil checks + zero | Option<T> | | |
| | Type inference | runtime | TS compile-time | yes | yes (strong) | | |
| | Numeric overflow | arbitrary int | IEEE-754 number | wraps (math/checked) | wraps (checked_*) | | |
| | Strings | unicode | UTF-16 | UTF-8 byte slice | UTF-8 str | | |
| | Memory mgmt | GC (refcount) | GC | GC | ownership (no GC) | | |
| ''' | |
| _TRANSPILE_STRATEGY = '''"""Transpilation Strategy Template. | |
| 7-step pipeline để dịch code giữ nguyên ngữ nghĩa. | |
| Author: Hieu Louis (2026) | |
| """ | |
| from __future__ import annotations | |
| from dataclasses import dataclass | |
| from typing import Any, Dict, List, Tuple | |
| @dataclass | |
| class TranslationConfig: | |
| source_lang: str | |
| target_lang: str | |
| source_version: str = "latest" | |
| target_version: str = "latest" | |
| mode: str = "idiomatic" # "idiomatic" | "literal" | "conservative" | |
| preserve_comments: bool = True | |
| rewrite_stdlib_calls: bool = True | |
| emit_tests: bool = True | |
| @dataclass | |
| class TranslationReport: | |
| warnings: List[str] | |
| manual_review_required: List[str] | |
| library_substitutions: Dict[str, str] | |
| confidence: float # 0.0 - 1.0 | |
| def translate(source: str, config: TranslationConfig) -> Tuple[str, TranslationReport]: | |
| """7-step transpilation pipeline. | |
| Returns: (translated_code, report) | |
| """ | |
| # 1. Parse source -> AST | |
| ast = _parse(source, config.source_lang) | |
| # 2. Type inference (best-effort) if target is statically typed | |
| if config.target_lang in {"go", "rust", "java", "c++", "c#"}: | |
| ast = _infer_types(ast) | |
| # 3. Idiom mapping (list comprehension -> map/filter, etc.) | |
| ast = _map_idioms(ast, config) | |
| # 4. Library substitution (requests -> httpx/fetch/reqwest) | |
| if config.rewrite_stdlib_calls: | |
| ast = _rewrite_stdlib(ast, config) | |
| # 5. Error model translation (try/except -> Result/Option or try/catch) | |
| ast = _translate_error_model(ast, config) | |
| # 6. Code generation | |
| code = _generate(ast, config.target_lang) | |
| # 7. Format (ruff / gofmt / rustfmt / prettier) | |
| formatted = _format(code, config.target_lang) | |
| report = TranslationReport( | |
| warnings=[], | |
| manual_review_required=[], | |
| library_substitutions={}, | |
| confidence=0.85, | |
| ) | |
| return formatted, report | |
| def _parse(src: str, lang: str): | |
| """Stub: dispatch to tree-sitter / libcst / babel / etc.""" | |
| ... | |
| def _infer_types(ast): | |
| """Stub: optional type inference for statically-typed targets.""" | |
| return ast | |
| def _map_idioms(ast, cfg): | |
| """Stub: rewrite idioms (comprehension -> map/filter, etc.).""" | |
| return ast | |
| def _rewrite_stdlib(ast, cfg): | |
| """Stub: replace source-stdlib calls with target-stdlib equivalents.""" | |
| return ast | |
| def _translate_error_model(ast, cfg): | |
| """Stub: convert try/except to Result/Option or try/catch.""" | |
| return ast | |
| def _generate(ast, lang: str) -> str: | |
| """Stub: emit code from AST.""" | |
| return "" | |
| def _format(code: str, lang: str) -> str: | |
| """Stub: invoke language formatter (ruff / gofmt / rustfmt / prettier).""" | |
| return code | |
| ''' | |