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Model: bhavinjawade/SOLAR-10B-OrcaDPO-Jawade
Source: Original Platform

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README.md

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+---
+license: mit
+datasets:
+- Intel/orca_dpo_pairs
+---
+
+## SOLAR-10B-OrcaDPO-Jawade
+
+### Overview
+This model card is instruction finetuned version of `upstage/SOLAR-10.7B-Instruct-v1.0` model. Trained on the Intel DPO Orca dataset using LoRA. Though it should be noted SOLAR-10.7B paper states that the 
+original model for alignment was trained on Intel ORCA DPO pairs. Retraining using DPO and LoRA shows slight (<1%) improvement on OpenLLM Leaderboard benchmarks against `SOLAR 10.7B-Instruct` and significant over `SOLAR 10.7B`
+
+![model_card_image](SOLAR_ORCA.png)
+
+## How to Use This Model
+
+To use the model `bhavinjawade/SOLAR-10B-OrcaDPO-Jawade`, follow these steps:
+
+1. **Import and Load the Model and Tokenizer**
+   Begin by importing the model and tokenizer. Load them using the `from_pretrained` method.
+
+   ```python
+   from transformers import AutoModelForCausalLM, AutoTokenizer
+   model = AutoModelForCausalLM.from_pretrained("bhavinjawade/SOLAR-10B-OrcaDPO-Jawade")
+   tokenizer = AutoTokenizer.from_pretrained("bhavinjawade/SOLAR-10B-OrcaDPO-Jawade")
+   ```
+
+2. **Format the Prompt**
+Format the chat input as a list of messages, each with a role ('system' or 'user') and content.
+
+    ```python
+    message = [
+        {"role": "system", "content": "You are a helpful assistant chatbot."},
+        {"role": "user", "content": "Is the universe real? or is it a simulation? whats your opinion?"}
+    ]
+    prompt = tokenizer.apply_chat_template(message, add_generation_prompt=True, tokenize=False)
+    ```
+
+3. **Create a Pipeline**
+Set up a pipeline for text generation with the loaded model and tokenizer.
+
+    ```python
+    pipeline = transformers.pipeline(
+        "text-generation",
+        model=model,
+        tokenizer=tokenizer
+    )
+    ```
+
+4. **Generate Text**
+Use the pipeline to generate a sequence of text based on the prompt. You can adjust parameters like temperature and top_p for different styles of responses.
+
+   ```python
+   sequences = pipeline(
+         prompt,
+         do_sample=True,
+       temperature=0.7,
+          top_p=0.9,
+          num_return_sequences=1,
+          max_length=200,
+      )
+    print(sequences[0]['generated_text'])
+    ```
+
+This setup allows you to utilize the capabilities of the **bhavinjawade/SOLAR-10B-OrcaDPO-Jawade** model for generating responses to chat inputs.
+
+### License
+- **Type**: MIT License
+- **Details**: This license permits reuse, modification, and distribution for both private and commercial purposes under the terms of the MIT License.
+
+### Model Details
+- **Model Name**: SOLAR-10.7B-Instruct-v1.0
+- **Organization**: Upstage
+- **Training Dataset**: Intel/orca_dpo_pairs
+- **Technique Used**: LoRA (Low-Rank Adaptation)
+
+### Contact Information
+- https://bhavinjawade.github.io

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+  "_name_or_path": "upstage/SOLAR-10.7B-Instruct-v1.0",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "torch_dtype": "float16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

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+  "pad_token_id": 2,
+  "transformers_version": "4.36.2",
+  "use_cache": false
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+}

special_tokens_map.json

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+{
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+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,43 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "1": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+    "2": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{% if message['content']%}{{'### System:\n' + message['content']+'\n\n'}}{% endif %}{% elif message['role'] == 'user' %}{{'### User:\n' + message['content']+'\n\n'}}{% elif message['role'] == 'assistant' %}{{'### Assistant:\n'  + message['content']}}{% endif %}{% if loop.last and add_generation_prompt %}{{ '### Assistant:\n' }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}