Instructions to use rustformers/redpajama-7b-ggml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rustformers/redpajama-7b-ggml with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rustformers/redpajama-7b-ggml")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rustformers/redpajama-7b-ggml", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use rustformers/redpajama-7b-ggml with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rustformers/redpajama-7b-ggml" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rustformers/redpajama-7b-ggml", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rustformers/redpajama-7b-ggml
- SGLang
How to use rustformers/redpajama-7b-ggml 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 "rustformers/redpajama-7b-ggml" \ --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": "rustformers/redpajama-7b-ggml", "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 "rustformers/redpajama-7b-ggml" \ --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": "rustformers/redpajama-7b-ggml", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rustformers/redpajama-7b-ggml with Docker Model Runner:
docker model run hf.co/rustformers/redpajama-7b-ggml
GGML converted versions of Together's RedPajama models
RedPajama-INCITE-7B-Base
RedPajama-INCITE-7B-Base was developed by Together and leaders from the open-source AI community including Ontocord.ai, ETH DS3Lab, AAI CERC, Université de Montréal, MILA - Québec AI Institute, Stanford Center for Research on Foundation Models (CRFM), Stanford Hazy Research research group and LAION. The training was done on 3,072 V100 GPUs provided as part of the INCITE 2023 project on Scalable Foundation Models for Transferrable Generalist AI, awarded to MILA, LAION, and EleutherAI in fall 2022, with support from the Oak Ridge Leadership Computing Facility (OLCF) and INCITE program.
- Base Model: RedPajama-INCITE-7B-Base
- Instruction-tuned Version: RedPajama-INCITE-7B-Instruct
- Chat Version: RedPajama-INCITE-7B-Chat
Model Details
- Developed by: Together Computer.
- Model type: Language Model
- Language(s): English
- License: Apache 2.0
- Model Description: A 6.9B parameter pretrained language model.
Converted Models:
Usage
Python via llm-rs:
Installation
Via pip: pip install llm-rs
Run inference
from llm_rs import AutoModel
#Load the model, define any model you like from the list above as the `model_file`
model = AutoModel.from_pretrained("rustformers/redpajama-7b-ggml",model_file="RedPajama-INCITE-7B-Base-q4_0-ggjt.bin")
#Generate
print(model.generate("The meaning of life is"))
Using local.ai GUI
Installation
Download the installer at www.localai.app.
Running Inference
Download your preferred model and place it in the "models" directory. Subsequently, you can start a chat session with your model directly from the interface.
Rust via Rustformers/llm:
Installation
git clone --recurse-submodules https://github.com/rustformers/llm.git
cd llm
cargo build --release
Run inference
cargo run --release -- gptneox infer -m path/to/model.bin -p "Tell me how cool the Rust programming language is:"
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