This model is continuously pretrained on OpenClaw .md files, making it highly specialized for understanding, explaining, and helping you work with the OpenClaw ecosystem.

You can ask things like:

How to set up OpenClaw
How to use OpenClaw with Docker
Debugging issues
Understanding configs, workflows, and usage

🧠 Model Details

Base Model: Mistral 7B
Training Type: Continuous Pretraining (LoRA Adapter)
Dataset: OpenClaw Markdown files (.md)
Framework: Unsloth + Hugging Face Transformers
Optimization: 4-bit quantization support

⚡ Quick Start (Inference Code)

python

from unsloth import FastLanguageModel
import torch

max_seq_length = 2048  # Supports RoPE scaling internally
dtype = None           # Auto detect (Float16 / BFloat16)
load_in_4bit = True    # Reduce memory usage

from transformers import TextStreamer

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="unsloth/mistral-7b-v0.3",
    max_seq_length=2048,
)

# Load OpenClaw adapter
model.load_adapter("Ishant06/OpenClaw-Continuous-Pretraining")

# Device setup
device = "cuda" if torch.cuda.is_available() else "cpu"

# ---- TEST INPUT ----
prompt = "how to use openclaw with docker?"

inputs = tokenizer(
    prompt,
    return_tensors="pt"
).to(device)

# Generate output
outputs = model.generate(
    **inputs,
    max_new_tokens=2048,
    temperature=0.7,
    top_p=0.9,
    do_sample=True,
)

# Decode response
response = tokenizer.decode(outputs[0], skip_special_tokens=True)

print("\n=== RESPONSE ===\n")
print(response)

🔥 Features

📚 Trained on real OpenClaw documentation
⚡ Fast inference using Unsloth
🧠 Better understanding of structured .md data
💻 Efficient on low VRAM (4-bit quantization)

🛠️ Use Cases

OpenClaw documentation assistant
Developer Q&A bot
Debugging and setup guidance
Learning OpenClaw faster

📌 Notes

This is a LoRA adapter, not a full standalone model
Requires base model: unsloth/mistral-7b-v0.3
Best suited for OpenClaw-related queries

⭐ Support

If you find this useful:

⭐ Star the repo
🤝 Share with others
🛠️ Contribute improvements

Uploaded model

Developed by: Ishant06
License: apache-2.0
Finetuned from model : unsloth/mistral-7b-v0.3-bnb-4bit

This mistral model was trained 2x faster with Unsloth

Ishant06/openclaw-continuous-pretraining

🚀 OpenClaw Continuous Pretraining Model (README.md)

👉 Try it instantly on Colab: Open In Colab

💡 Ask anything about OpenClaw