Instructions to use hailsbop/Mistral-7b-v2-hv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hailsbop/Mistral-7b-v2-hv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hailsbop/Mistral-7b-v2-hv2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hailsbop/Mistral-7b-v2-hv2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use hailsbop/Mistral-7b-v2-hv2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hailsbop/Mistral-7b-v2-hv2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hailsbop/Mistral-7b-v2-hv2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hailsbop/Mistral-7b-v2-hv2
- SGLang
How to use hailsbop/Mistral-7b-v2-hv2 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 "hailsbop/Mistral-7b-v2-hv2" \ --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": "hailsbop/Mistral-7b-v2-hv2", "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 "hailsbop/Mistral-7b-v2-hv2" \ --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": "hailsbop/Mistral-7b-v2-hv2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hailsbop/Mistral-7b-v2-hv2 with Docker Model Runner:
docker model run hf.co/hailsbop/Mistral-7b-v2-hv2
Model Card for mistral-7b-hlx2
Model Summary
mistral-7b-hlx2 is a supervised fine-tuned (SFT) version of Mistral-7B-Instruct-v0.2, trained on cleaned, de-identified WhatsApp conversation logs (dataset: hailsbop/Haleyv2).
The model is optimized for interpersonal dialogue, conversational tone, and expressive communication.
Table of Contents
- Model Details
- Uses
- Bias, Risks, and Limitations
- Training Details
- Evaluation
- Societal Impact Assessment
- Model Examination
- Environmental Impact
- Technical Specifications
- Citation
- Glossary
- More Information
- Model Card Authors
- Model Card Contact
- How to Get Started
Model Details
Model Description
mistral-7b-hlx2 is a decoder-only transformer model fine-tuned via SFT using WhatsApp-derived conversational data.
- Developed by: Haley
- License: Apache-2.0
- Fine-tuned From: mistralai/Mistral-7B-Instruct-v0.2
- Dataset: hailsbop/Haleyv2
Uses
Direct Use
Conversational agents, expressive dialogue, creative writing.
Downstream Use
Persona-aligned chatbots, stylistic generation.
Out-of-Scope
Safety-critical use, factual decision-making, impersonation.
Bias, Risks, and Limitations
This model reflects interpersonal tone, subjectivity, and informal WhatsApp communication patterns. Not suited for factual accuracy.
Training Details
Training Data
Dataset: hailsbop/Haleyv2 — de-identified WhatsApp logs.
Preprocessing
PII removed, paired into instruction–response sets.
Training Procedure
Full SFT, mixed precision, AdamW optimizer.
Evaluation
Qualitative testing only — no benchmarks.
Environmental Impact
Training CO₂ impact not recorded.
Technical Specifications
- 7B parameter decoder LM
- FlashAttention-like optimizations
- Causal LM objective
Citation
@misc{mistral7bhlx2,
title={mistral-7b-hlx2},
author={Haley},
year={2025},
howpublished={https://huggingface.co/hailsbop/mistral-7b-hlx2}
}
Model Card Authors
Haley
Model tree for hailsbop/Mistral-7b-v2-hv2
Base model
mistralai/Mistral-7B-Instruct-v0.2