MehdiHosseiniMoghadam
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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### Model
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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### Downstream Use [optional]
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### Out-of-Scope Use
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[More Information Needed]
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[
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## How to Get Started with the Model
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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# AVA-Qwen1.5-7
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Fine-Tuned Qwen1.5 7B Persian Large Language Model LLM / Persian Qwen1.5 7B
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# AVA-Qwen1.5 / Persian Qwen
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<img src="Qwen15.png" height="600" width="940" >
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### This Repository Contains Documents for Fine-Tuned Qwen1.5 Persian Large Language Model(LLM) Called AVA-Qwen1.5
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(Still in progress)
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-------------------------------------------------
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### Dataset used:
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To Be Done
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-------------------------------------------------
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### Usage:
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All models are hosted in HuggingFace, and here is the code for inference:
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```py
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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import torch
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model_name_or_id = "MehdiHosseiniMoghadam/AVA-Qwen1.5-7B-Chat"
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model = AutoModelForCausalLM.from_pretrained(model_name_or_id, torch_dtype=torch.float16, device_map="auto", low_cpu_mem_usage=True, load_in_8bit=True)
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tokenizer = AutoTokenizer.from_pretrained(model_name_or_id)
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prompt = ''
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prompt = f"### Human:{prompt}\n### Assistant:"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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generation_config = GenerationConfig(
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do_sample=True,
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top_k=1,
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temperature=0.01,
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max_new_tokens=90,
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pad_token_id=tokenizer.eos_token_id
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)
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outputs = model.generate(**inputs, generation_config=generation_config)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## License
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[![License](https://img.shields.io/badge/license-MIT-blue.svg)](/LICENSE)
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Released Jan 30, 2024 by [Mehdi Hosseini Moghadam](https://github.com/mehdihosseinimoghadam)
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Attention ⚠️: The user is responsible for using AVA-Llama-3 / Persian Llama 3
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Any misuse of the model (of any kind) is the responsibility of the user and not the creator
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## Contact
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<a href="https://ir.linkedin.com/in/mehdi-hosseini-moghadam-384912198" target="_blank"><img src="https://cdn-icons.flaticon.com/png/512/3536/premium/3536505.png?token=exp=1644871115~hmac=59bc0b44906adebd63f84642086d4695" alt="Buy Me A Coffee" style="height: 50px !important;width: 50px !important;box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;-webkit-box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;" ></a>
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<a href="https://scholar.google.com/citations?user=TKWbohsAAAAJ&hl=en" target="_blank"><img src="https://cdn-icons.flaticon.com/png/512/3107/premium/3107171.png?token=exp=1644871560~hmac=7f8fd85e8db71945e25202a3ac739e1c" alt="Buy Me A Coffee" style="height: 50px !important;width: 50px !important;box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;-webkit-box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;" ></a>
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<a href="https://huggingface.co/MehdiHosseiniMoghadam" target="_blank"><img src="https://cdn-icons.flaticon.com/png/512/2461/premium/2461892.png?token=exp=1644871873~hmac=8659d04d69008e399a5344cad5bc4270" alt="Buy Me A Coffee" style="height: 50px !important;width: 50px !important;box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;-webkit-box-shadow: 0px 3px 2px 0px rgba(190, 190, 190, 0.5) !important;" ></a>
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