Instructions to use rishanthrajendhran/IdeaLens with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

rishanthrajendhran commited on Aug 31

Commit

c1ec400

verified ·

1 Parent(s): 74bf9a1

LoRA adapter over nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Browse files

Files changed (3) hide show

README.md +37 -0
adapter_config.json +38 -0
adapter_model.safetensors +3 -0

README.md ADDED Viewed

	@@ -0,0 +1,37 @@

+---
+base_model: nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
+library_name: peft
+tags:
+- tinker
+- peft
+- lora
+- base_model:adapter:nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
+tinker_path: tinker://9f500a21-df39-5716-89e5-e65f9390fb14:train:0/sampler_weights/nemo_full_v1m_r64_ep1_final
+---
+# Tinker LoRA Adapter
+This repository contains a LoRA adapter exported from Tinker.
+## Usage
+```python
+from transformers import AutoModelForCausalLM
+adapter_id = "rishanthrajendhran/ideadet-nemotron30b-1m-outline"
+base_model = "nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16"
+model = AutoModelForCausalLM.from_pretrained(adapter_id, device_map="auto")
+```
+## Source
+```
+tinker://9f500a21-df39-5716-89e5-e65f9390fb14:train:0/sampler_weights/nemo_full_v1m_r64_ep1_final
+```
+## Details
+- Base model: nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16
+- LoRA rank: 64
+- Trained modules: attn=True, mlp=True, unembed=True

adapter_config.json ADDED Viewed

	@@ -0,0 +1,38 @@

+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": false,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": "all-linear",
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

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+size 3088638968