SSTalha
/

Fashion_PHI_1-5

@@ -1,215 +1,54 @@
 ---
 library_name: peft
-base_model: typeof/phi-1_5
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
 ### Model Description
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 ## How to Get Started with the Model
-Use the code below to get started with the model.
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-## Training procedure
-### Framework versions
-- PEFT 0.6.0
-## Training procedure
-### Framework versions
-- PEFT 0.6.0

 ---
+license: mit
 library_name: peft
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- nlp
+- code
 ---
 ### Model Description
+- **Developed by:** [Microsoft]
+- **Model type:** [Text Generation]
+- **Finetuned from model** [microsoft/phi-1_5]
+## How to Use
+Phi-1.5 has been integrated in the transformers version 4.30.0. ensure that you are doing the following:
+* When loading the model, ensure that trust_remote_code=True is passed as an argument of the from_pretrained() function.
+### Intended Uses
+Given the nature of the training data, Fashion Phi-1.5 is best suited for prompts using the QA format, the chat format. Note that Fashion Phi-1.5 often produces irrelevant text following the main answer. In the following example, we've truncated the answer for illustrative purposes only.
+## QA
+```markdown
+<human>: What can I wear with an olive green bomber jacket for a winter casual outing? Olive Male
+<assistant>: Great choice! To wear with an olive green bomber jacket for a winter casual outing consider adding: 1. White or gray graphic T-shirt for a laid-back vibe. 2. Dark denim jeans or cargo pants for a rugged look. 3. High-top sneakers or combat boots for a street-style finish. 4. A plaid flannel shirt or denim jacket for added warmth. 5. A patterned scarf or beanie for a pop of color and style.
+```
 ## How to Get Started with the Model
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+torch_device = 'cuda' if torch.cuda.is_available() else 'cpu'
+Model = 'SSTalha/Fashion_Phi-1_5'
+model = AutoModelForCausalLM.from_pretrained(Model, torch_dtype="auto", trust_remote_code=True).to(torch_device)
+tokenizer = AutoTokenizer.from_pretrained(Model, trust_remote_code=True)
+inputs = tokenizer('''<human>: Have black dress pants and need advice on a shirt for a semi-formal gathering. Any recommendations on colors and styles? Black Male ''', return_tensors="pt", return_attention_mask=False)
+inputs = {key: value.to('cuda') for key, value in inputs.items()}
+outputs = model.generate(**inputs, max_length=90)
+text = tokenizer.batch_decode(outputs)[0]
+print(text)
+```