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

Libraries

How to use dhruvchandra/BlogGeneration with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
model = PeftModel.from_pretrained(base_model, "dhruvchandra/BlogGeneration")

Transformers

How to use dhruvchandra/BlogGeneration with Transformers:

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

pipe = pipeline("text-generation", model="dhruvchandra/BlogGeneration")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("dhruvchandra/BlogGeneration", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use dhruvchandra/BlogGeneration with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dhruvchandra/BlogGeneration"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dhruvchandra/BlogGeneration",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dhruvchandra/BlogGeneration

SGLang

How to use dhruvchandra/BlogGeneration 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 "dhruvchandra/BlogGeneration" \
    --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": "dhruvchandra/BlogGeneration",
		"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 "dhruvchandra/BlogGeneration" \
        --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": "dhruvchandra/BlogGeneration",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use dhruvchandra/BlogGeneration with Docker Model Runner:
```
docker model run hf.co/dhruvchandra/BlogGeneration
```

Model Card for Model ID

Blog Generation on Data Science, Machine Learning, Gen AI Advancements..

Model Details

Primarily built for personal application deployment. Will keep upgrading and increase data. Feel free to test out your apps.

Model Description

Developed by: Dhruv Chandra
Funded by [optional]: Dhruv Chandra
Model type: text-generation
Language(s) (NLP): English
Finetuned from model [optional]: mistralai/Mistral-7B-Instruct-v0.1

Uses

Blog Generation

Direct Use

Blog Upload on Wordpress

How to Get Started with the Model

Use the code below to get started with the model.


from transformers import pipeline

pipe = pipeline("text-generation", model="dhruvchandra/BlogGeneration") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)

Training Details

Training Data

Self Prepared Data on Blogs scraped from open posts.

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

Hardware Type: T4 GPU
Hours used: 3-4
Cloud Provider: Hugging Face
Compute Region: India

[More Information Needed]

Framework versions

PEFT 0.16.0

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Model tree for dhruvchandra/BlogGeneration

Base model

mistralai/Mistral-7B-v0.1

Finetuned

mistralai/Mistral-7B-Instruct-v0.1

Adapter

(441)

this model

Paper for dhruvchandra/BlogGeneration

Quantifying the Carbon Emissions of Machine Learning

Paper • 1910.09700 • Published Oct 21, 2019 • 62