Instructions to use RainbowLord/Rainbow-AI-Coder-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RainbowLord/Rainbow-AI-Coder-it with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="RainbowLord/Rainbow-AI-Coder-it")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RainbowLord/Rainbow-AI-Coder-it")
model = AutoModelForCausalLM.from_pretrained("RainbowLord/Rainbow-AI-Coder-it", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use RainbowLord/Rainbow-AI-Coder-it with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RainbowLord/Rainbow-AI-Coder-it"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RainbowLord/Rainbow-AI-Coder-it",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/RainbowLord/Rainbow-AI-Coder-it

SGLang

How to use RainbowLord/Rainbow-AI-Coder-it 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 "RainbowLord/Rainbow-AI-Coder-it" \
    --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": "RainbowLord/Rainbow-AI-Coder-it",
		"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 "RainbowLord/Rainbow-AI-Coder-it" \
        --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": "RainbowLord/Rainbow-AI-Coder-it",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use RainbowLord/Rainbow-AI-Coder-it with Docker Model Runner:
```
docker model run hf.co/RainbowLord/Rainbow-AI-Coder-it
```

Model Card for Model ID

This is Rainbow Coder, it is an alternative Rainbow AI model for specialist, but not WebLLM or MLC based. It follows 'it' like google/codegemma-7b.

Model Details

Model Description

Developed by: Rainbowlord16
Model type: it
License: apache 2.0
Finetuned from model: google/codegemma-7b

Uses

We inten you to use it as Rainbow-Coder, mainly for code and please don't abuse or waste token usage.

[More Information Needed]

Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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Training Procedure

Preprocessing [optional]

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Training Hyperparameters

Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Model Examination [optional]

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Hardware Type: [More Information Needed]
Hours used: [More Information Needed]
Cloud Provider: [More Information Needed]
Compute Region: [More Information Needed]
Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

BibTeX:

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APA:

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Glossary [optional]

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Safetensors

Model size

9B params

Tensor type

BF16

Model tree for RainbowLord/Rainbow-AI-Coder-it

Base model

google/codegemma-7b

Quantized

(7)

this model

Paper for RainbowLord/Rainbow-AI-Coder-it

Quantifying the Carbon Emissions of Machine Learning

Paper • 1910.09700 • Published Oct 21, 2019 • 61