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Jagneshdeveloper
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Model Details
Model Provider
Jagneshdeveloper
Model Tree
Qwen/Qwen2.5-7B
Input Modalities
Output Modalities
Supported Functionality
📄 License: Apache 2.0 | ⚙️ Parameters: 7 Billion | 💻 Focus: Coding & Agents
Prakrit1.0-7B-Small is an advanced 7-billion parameter large language model proudly developed by Jagneshdeveloper. Built on top of the powerful Qwen2.5 architecture, this model has been custom-engineered and fine-tuned specifically for autonomous agentic workflows and elite coding tasks.
By optimizing the baseline capabilities, Prakrit1.0-7B-Small delivers rapid, highly accurate code synthesis and structured logical reasoning.
You can quickly load and deploy Prakrit1.0-7B-Small using the Hugging Face transformers library:
python
from transformers import AutoModelForCausalLM, AutoTokenizerimport torchmodel_name = "Jagneshdeveloper/prakrit1.0-7b-small"# Load the optimized tokenizer and modeltokenizer = AutoTokenizer.from_pretrained(model_name)model = AutoModelForCausalLM.from_pretrained(model_name,device_map="auto",torch_dtype=torch.bfloat16)# Test prompt for coding/agentic workflowprompt = "Write a Python script to scrape website data and format it into a structured JSON array."inputs = tokenizer(prompt, return_tensors="pt").to("cuda")outputs = model.generate(**inputs, max_new_tokens=300, temperature=0.3)print(tokenizer.decode(outputs, skip_special_tokens=True))
Created with ❤️ by Jagneshdeveloper in India. This model is distributed under the Apache 2.0 license. For feedback, feature requests, or collaborations, feel free to open a discussion in the community tab!