Update README.md

README.md

@@ -1,97 +0,0 @@
----
-license: apache-2.0
-base_model: bn22/Mistral-7B-Instruct-v0.1-sharded
-tags:
-- generated_from_trainer
-model-index:
-- name: outputs
-  results: []
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# UrduNewsMistral7B
-
-This model is a fine-tuned version of [bn22/Mistral-7B-Instruct-v0.1-sharded](https://huggingface.co/bn22/Mistral-7B-Instruct-v0.1-sharded) on [Urdu-Instruct-News-Article-Generation](https://huggingface.co/datasets/AhmadMustafa/Urdu-Instruct-News-Article-Generation) dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.1925
-
-## Usage
-Here is an example of how you would load:
-```python
-import torch
-from peft import PeftModel    
-from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
-
-model_name = "bn22/Mistral-7B-Instruct-v0.1-sharded"
-adapters_name = 'mwz/UrduNewsMistral7B'
-
-model = AutoModelForCausalLM.from_pretrained(
-    model_name,
-    load_in_4bit=True,
-    torch_dtype=torch.bfloat16,
-    device_map="auto",
-    max_memory= {i: '24000MB' for i in range(torch.cuda.device_count())},
-    quantization_config=BitsAndBytesConfig(
-        load_in_4bit=True,
-        bnb_4bit_compute_dtype=torch.bfloat16,
-        bnb_4bit_use_double_quant=True,
-        bnb_4bit_quant_type='nf4'
-    ),
-)
-model = PeftModel.from_pretrained(model, adapters_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-```
-Inference can then be performed as usual with HF models as follows:
-```python
-prompt = "پیٹرول کی قیمت میں 2روپے 50 پیسے اضافہ"
-formatted_prompt = (
-    f"اس دی گی ایک خبر سے متعلق ایک مضمون لکھیں"
-    f"### Human: {prompt} ### Assistant:"
-)
-inputs = tokenizer(formatted_prompt, return_tensors="pt").to("cuda:0")
-outputs = model.generate(inputs=inputs.input_ids, max_new_tokens=20)
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
-```
-Expected output similar to the following:
-```
-اس دی گی ایک خبر سے متعلق ایک مضمون لکھیں۔ خبر:### Human:  پیٹرول کی قیمت میں 2روپے 50 پیسے اضافہ ### Assistant: بہترین پیٹرول کے ان
-```
-
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0002
-- train_batch_size: 16
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 64
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_ratio: 0.05
-- num_epochs: 50
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 1.1387        | 5.71  | 10   | 1.2070          |
-| 0.9337        | 11.43 | 20   | 1.1634          |
-| 0.8676        | 17.14 | 30   | 1.1697          |
-| 0.8065        | 22.86 | 40   | 1.1868          |
-| 0.7759        | 28.57 | 50   | 1.1925          |
-
-
-### Framework versions
-
-- Transformers 4.36.0.dev0
-- Pytorch 2.1.0+cu121
-- Datasets 2.15.0
-- Tokenizers 0.15.0