Name | llama-index-embeddings-nvidia JSON |
Version |
0.1.3
JSON |
| download |
home_page | None |
Summary | llama-index embeddings nvidia integration |
upload_time | 2024-05-18 16:09:12 |
maintainer | None |
docs_url | None |
author | Your Name |
requires_python | <4.0,>=3.8.1 |
license | MIT |
keywords |
|
VCS |
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bugtrack_url |
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requirements |
No requirements were recorded.
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Travis-CI |
No Travis.
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coveralls test coverage |
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# NVIDIA's Embeddings connector
With this connector, you'll be able to connect to and generate from compatible models available as hosted [NVIDIA NIMs](https://ai.nvidia.com), such as:
- NVIDIA's Retrieval QA Embedding Model [embed-qa-4](https://build.nvidia.com/nvidia/embed-qa-4)
_First_, get a free API key. Go to https://build.nvidia.com, select a model, click "Get API Key".
Store this key in your environment as `NVIDIA_API_KEY`.
## Installation
```bash
pip install llama-index-embeddings-nvidia
```
## Usage
```python
from llama_index.embeddings.nvidia import NVIDIAEmbedding
embedder = NVIDIAEmbedding()
embedder.get_query_embedding("What's the weather like in Komchatka?")
```
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"description": "# NVIDIA's Embeddings connector\n\nWith this connector, you'll be able to connect to and generate from compatible models available as hosted [NVIDIA NIMs](https://ai.nvidia.com), such as:\n\n- NVIDIA's Retrieval QA Embedding Model [embed-qa-4](https://build.nvidia.com/nvidia/embed-qa-4)\n\n_First_, get a free API key. Go to https://build.nvidia.com, select a model, click \"Get API Key\".\nStore this key in your environment as `NVIDIA_API_KEY`.\n\n## Installation\n\n```bash\npip install llama-index-embeddings-nvidia\n```\n\n## Usage\n\n```python\nfrom llama_index.embeddings.nvidia import NVIDIAEmbedding\n\nembedder = NVIDIAEmbedding()\nembedder.get_query_embedding(\"What's the weather like in Komchatka?\")\n```\n",
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