Ishant06/openclaw-continuous-pretraining

🚀 OpenClaw Continuous Pretraining Model (README.md)

👉 Try it instantly on Colab:

💡 Ask anything about OpenClaw

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

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🧠 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

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⚡ Quick Start (Inference Code)

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)

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🔥 Features

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

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🛠️ Use Cases

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

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📌 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

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⭐ 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