Text Generation
Transformers
Safetensors
English
nemotron_h
ai-text-detection
idea-provenance
conversational
Instructions to use rishanthrajendhran/IdeaLens with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rishanthrajendhran/IdeaLens with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rishanthrajendhran/IdeaLens") 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("rishanthrajendhran/IdeaLens") model = AutoModelForCausalLM.from_pretrained("rishanthrajendhran/IdeaLens", 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 rishanthrajendhran/IdeaLens with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rishanthrajendhran/IdeaLens" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rishanthrajendhran/IdeaLens", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/rishanthrajendhran/IdeaLens
- SGLang
How to use rishanthrajendhran/IdeaLens 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 "rishanthrajendhran/IdeaLens" \ --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": "rishanthrajendhran/IdeaLens", "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 "rishanthrajendhran/IdeaLens" \ --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": "rishanthrajendhran/IdeaLens", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use rishanthrajendhran/IdeaLens with Docker Model Runner:
docker model run hf.co/rishanthrajendhran/IdeaLens
Commit History
8 days ago
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Card: remove the access-request prompt (the repo is not gated)
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Card: cite the arXiv paper (2610.06778)
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10 days ago
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Card: link the demo (http://ideadetector.ai/)
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12 days ago
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Card: demo placeholder (link TBD)
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13 days ago
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Card: run without a GPU on Tinker
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Card: link the IdeaLens collection
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Card: quick start with the idealens package (classify, extract, score)
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Card: link the idealens package and GitHub repo
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Rename the corpus IdeaLens-1M -> WildOutlines
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Card: strict '<' flag rule, format-assignment wording, vLLM section; thresholds.json flag rule
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17 days ago
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Release: merged weights, adapter/ (Tinker LoRA), load_adapter.py, thresholds, card, LICENSE
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model card
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LoRA adapter over nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
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initial commit
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