Text Generation
Transformers
Safetensors
English
babylm
babylm-2026
mixture-of-experts
msit
xpertgpt
custom_code
Instructions to use anonym5035/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anonym5035/temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="anonym5035/temp", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anonym5035/temp", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use anonym5035/temp with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "anonym5035/temp" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "anonym5035/temp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/anonym5035/temp
- SGLang
How to use anonym5035/temp 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 "anonym5035/temp" \ --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": "anonym5035/temp", "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 "anonym5035/temp" \ --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": "anonym5035/temp", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use anonym5035/temp with Docker Model Runner:
docker model run hf.co/anonym5035/temp
Soham Jain
Update strict-small architecture files (sliding window [64, 16, 8, 4], ln3, ln_post_moe, no res3)
3a7a00c verified | import os | |
| import sys | |
| import re | |
| import argparse | |
| from huggingface_hub import HfApi | |
| def upload_project(repo_name=None): | |
| token = os.environ.get("HF_TOKEN") | |
| if not token: | |
| print("Error: HF_TOKEN environment variable not set!") | |
| print("Please set it before running: set HF_TOKEN=your_token") | |
| sys.exit(1) | |
| if not repo_name: | |
| repo_name = os.environ.get("HF_REPO_NAME", "temp") | |
| local_dir = os.path.dirname(os.path.abspath(__file__)) | |
| api = HfApi(token=token) | |
| try: | |
| user_info = api.whoami() | |
| username = user_info["name"] | |
| print(f"[HF] Authenticated as: {username}") | |
| except Exception as e: | |
| print(f"[HF] Authentication failed: {e}") | |
| sys.exit(1) | |
| repo_id = f"{username}/{repo_name}" | |
| print(f"[HF] Uploading modified sliding-window strict-small scripts to '{repo_id}' main branch...") | |
| ignore_patterns = [ | |
| "**/__pycache__/*", | |
| "**/*.pyc", | |
| "**/hf_cache/*", | |
| "**/nltk_data/*", | |
| "**/checkpoints/*" | |
| ] | |
| sensitive_ignores = [] | |
| token_pattern = re.compile(r"hf_[a-zA-Z0-9]{34}") | |
| for root, dirs, files in os.walk(local_dir): | |
| if "__pycache__" in root or "checkpoints" in root: | |
| continue | |
| for file in files: | |
| file_path = os.path.join(root, file) | |
| if file.endswith(('.bin', '.safetensors', '.zip', '.tar.gz', '.pkl')): | |
| continue | |
| try: | |
| with open(file_path, "r", errors="ignore") as f: | |
| content = f.read() | |
| if token_pattern.search(content): | |
| rel_path = os.path.relpath(file_path, local_dir) | |
| rel_path_glob = rel_path.replace("\\", "/") | |
| sensitive_ignores.append(rel_path_glob) | |
| print(f" -> Warning: Sensitive file containing raw token excluded: {rel_path_glob}") | |
| except Exception: | |
| pass | |
| all_ignores = ignore_patterns + sensitive_ignores | |
| try: | |
| api.upload_folder( | |
| folder_path=local_dir, | |
| repo_id=repo_id, | |
| repo_type="model", | |
| revision="main", | |
| ignore_patterns=all_ignores, | |
| commit_message="Update strict-small architecture files (sliding window [64, 16, 8, 4], ln3, ln_post_moe, no res3)" | |
| ) | |
| print(f"\n[HF] Success! Scripts uploaded to: https://huggingface.co/{repo_id}/tree/main") | |
| except Exception as e: | |
| print(f"[HF] Upload failed: {e}") | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--repo-name", type=str, default=None, help="Hugging Face repository name") | |
| args = parser.parse_args() | |
| upload_project(args.repo_name) | |