---
language:
- en
license: llama3.1
library_name: transformers
pipeline_tag: text-generation
tags:
- pearl
- llama
- llama-3.1
- instruct
- text-generation
- vllm
- mining
base_model: meta-llama/Llama-3.1-8B-Instruct
---

# pearl-ai/Llama-3.1-8B-Instruct-pearl

Pearl-certified variant of Llama-3.1-8B-Instruct, intended to run with the Pearl vLLM mining plugin.

- Project website: [https://pearlresearch.ai](https://pearlresearch.ai)
- Pearl repository: [https://github.com/pearl-research-labs/pearl](https://github.com/pearl-research-labs/pearl)
- Miner docs: [https://github.com/pearl-research-labs/pearl/tree/master/miner](https://github.com/pearl-research-labs/pearl/tree/master/miner)

## Model Details

- **Base model:** `meta-llama/Llama-3.1-8B-Instruct`
- **Model type:** Causal LLM (instruction-tuned)
- **Primary runtime target:** Pearl vLLM plugin (`miner/vllm-miner`)
- **Intended use:** Text generation with Pearl mining integration

## Intended Use

This model is intended to be served through the Pearl miner stack, where vLLM inference is integrated with Pearl mining workflows.

Typical flow:
1. Run `pearld` with RPC enabled.
2. Start the Pearl miner/vLLM stack.
3. Serve this model through vLLM while Pearl gateway/miner components handle mining-side integration.

## How To Use (Pearl vLLM Plugin)

Follow the miner setup from the Pearl repo:
- [pearl/miner README](https://github.com/pearl-research-labs/pearl/tree/master/miner)

High-level prerequisites:
- Python 3.12
- `uv`
- CUDA + NVIDIA GPU (sm90 class, e.g. H100/H200, per project docs)
- Rust toolchain
- Running `pearld` node with RPC credentials

### Docker Example

From the Pearl repository root:

```bash
docker buildx build -t vllm_miner . -f miner/vllm-miner/Dockerfile
```

```bash
docker run --rm -it --gpus all \
  -p 8000:8000 -p 8337:8337 -p 8339:8339 \
  -e PEARLD_RPC_URL=<PEARLD_URL> \
  -e PEARLD_RPC_USER=<RPC_USER> \
  -e PEARLD_RPC_PASSWORD=<RPC_PASSWORD> \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  --shm-size 8g \
  vllm_miner:latest \
  pearl-ai/Llama-3.1-8B-Instruct-pearl \
  --host 0.0.0.0 --port 8000 \
  --max-model-len 8192 \
  --gpu-memory-utilization 0.9 \
  --enforce-eager
```

## License

This model is a derivative of Llama 3.1 and is distributed under the Llama 3.1 license terms.

## Limitations

- Can generate incorrect, unsafe, or biased outputs.
- Requires careful deployment controls and output validation.
- Hardware/software compatibility depends on the Pearl miner stack and supported GPU architectures.