added training and peft params

README.md

@@ -1,8 +1,86 @@
 ---
 library_name: peft
+license: apache-2.0
+datasets:
+- knkarthick/dialogsum
+pipeline_tag: summarization
 ---
+## Useage with Transformers
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import transformers
+from peft import PeftModel
+
+# Quantization config
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype="float16",
+)
+
+model_name = "TinyPixel/Llama-2-7B-bf16-sharded"
+
+# loading the model with quantization config
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    quantization_config=bnb_config,
+    trust_remote_code=True,
+    device_map='auto'
+)
+
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True , return_token_type_ids=False)
+tokenizer.pad_token = tokenizer.eos_token
+
+model = PeftModel.from_pretrained(model,"shenoy/DialogSumLlama2_qlora", device_map="auto")
+
+text = """### Instruction: 
+Write a concise summary of the below input text.Return your response in bullet points which covers the key points of the text. 
+### Input: 
+#Person1#: Ms. Dawson, I need you to take a dictation for me.
+#Person2#: Yes, sir...
+#Person1#: This should go out as an intra-office memorandum to all employees by this afternoon. Are you ready?
+#Person2#: Yes, sir. Go ahead.
+#Person1#: Attention all staff... Effective immediately, all office communications are restricted to email correspondence and official memos. The use of Instant Message programs by employees during working hours is strictly prohibited.
+#Person2#: Sir, does this apply to intra-office communications only? Or will it also restrict external communications?
+#Person1#: It should apply to all communications, not only in this office between employees, but also any outside communications.
+#Person2#: But sir, many employees use Instant Messaging to communicate with their clients.
+#Person1#: They will just have to change their communication methods. I don't want any - one using Instant Messaging in this office. It wastes too much time! Now, please continue with the memo. Where were we?
+#Person2#: This applies to internal and external communications.
+#Person1#: Yes. Any employee who persists in using Instant Messaging will first receive a warning and be placed on probation. At second offense, the employee will face termination. Any questions regarding this new policy may be directed to department heads.
+#Person2#: Is that all?
+#Person1#: Yes. Please get this memo typed up and distributed to all employees before 4 pm.
+### Response :"""
+
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(input_ids=inputs['input_ids'], attention_mask=inputs['attention_mask'], max_new_tokens=100 ,repetition_penalty=1.2)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+---
+
 ## Training procedure
 
+Training Configuration:
+
+- `per_device_train_batch_size`: 4
+- `gradient_accumulation_steps`: 4
+- `optim`: "paged_adamw_8bit"
+- `learning_rate`: 2e-4
+- `lr_scheduler_type`: "linear"
+- `save_strategy`: "epoch"
+- `logging_steps`: 10
+- `num_train_epochs`: 2
+- `max_steps`: 50
+- `fp16`: True
+
+LORA Configuration:
+
+- `lora_alpha`: 16
+- `lora_dropout`: 0.05
+- `target_modules`: ["q_proj", "v_proj"]
+- `r`: 8
+- `bias`: "none"
+- `task_type`: "CAUSAL_LM"
 
 The following `bitsandbytes` quantization config was used during training:
 - load_in_8bit: False
@@ -14,7 +92,10 @@ The following `bitsandbytes` quantization config was used during training:
 - bnb_4bit_quant_type: nf4
 - bnb_4bit_use_double_quant: False
 - bnb_4bit_compute_dtype: float16
-### Framework versions
 
-
-- PEFT 0.4.0
+### Framework versions
+- `accelerate` 0.21.0
+- `peft` 0.4.0
+- `bitsandbytes` 0.40.2
+- `transformers` 4.30.2
+- `trl` 0.4.7