Instructions to use AijazForge/Manan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use AijazForge/Manan with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("AijazForge/Manan", set_active=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files---
title: Manan
author: AijazForge
language: en
license: apache-2.0
tags:
- text-generation
- language-model
- ai-assistant
---
# Manan
Manan is a fine-tuned language model developed by AijazForge, optimized for text generation and conversational applications. This model supports professional use cases including content creation, question answering, and code assistance. [web:38][web:15]
## Model Overview
- **Developer:** AijazForge
- **Architecture:** Transformer-based large language model.
- **Parameters:** [Insert parameter count, e.g., 7B].
- **Intended Applications:** Enterprise prototyping, educational tools, and developer workflows. [web:26]
## Usage Instructions
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "AijazForge/Manan"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
inputs = tokenizer("Describe neural networks:", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=150)
response = tokenizer.decode(outputs)
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license: apache-2.0
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---
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license: apache-2.0
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datasets:
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- bigai/TongSIM-Asset
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language:
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- en
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metrics:
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- accuracy
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- character
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base_model:
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- google/functiongemma-270m-it
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new_version: zai-org/GLM-4.7
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library_name: adapter-transformers
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tags:
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- agent
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- finance
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---
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