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Model: lxe/Cerebras-GPT-2.7B-Alpaca-SP
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+tags:
+- code
+---
+
+## Cerebras-GPT-2.7B-Alpaca-SP
+
+Cerebras-GPT-2.7B-Alpaca-SP is [cerebras/Cerebras-GPT-2.7B](https://huggingface.co/cerebras/Cerebras-GPT-2.7B) finetuned on a modified [Alpaca dataset](https://github.com/tloen/alpaca-lora/blob/main/alpaca_data_cleaned.json) with a shorter prompt structure (`Human:...\n\nAssistant:`). This contains the float16 model merged with [lxe/lora-cerebras-gpt2.7b-alpaca-shortprompt](https://huggingface.co/lxe/lora-cerebras-gpt2.7b-alpaca-shortprompt) LoRA.
+
+
+### Limitations:
+
+Although mostly coherent, the model tends to hallucinate signinficantly, often producing erroneous information.
+
+### Basic Usage:
+
+```python
+tokenizer = transformers.AutoTokenizer.from_pretrained('lxe/Cerebras-GPT-2.7B-Alpaca-SP')
+
+model = transformers.AutoModelForCausalLM.from_pretrained(
+    `lxe/Cerebras-GPT-2.7B-Alpaca-SP`,
+    load_in_8bit=True,
+    torch_dtype=torch.float16,
+    device_map={"": 0},
+)
+
+prompt = "Human: how old is the sun?\n\nAssistant:"
+input_ids = tokenizer.encode(prompt, return_tensors="pt").cuda()
+
+with torch.no_grad():
+    output = model.generate(
+        input_ids=input_ids,
+        max_length=100,
+        early_stopping=True,
+    )
+generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+print(generated_text)
+``` 
+
+```
+Human: how old is the sun?
+
+Assistant: The sun is approximately 4.5 billion years old.
+```
+
+### Example Outputs:
+
+**Human**: how old is the sun? <br />
+**Assistant**: The sun is approximately 4.5 billion years old.
+
+
+**Human**: what are the highest grossing films of the 2000-2010 decade? <br />
+**Assistant**: The highest grossing film in 2010 was Avatar, which earned $2.5 billion worldwide and is currently ranked as one of the top 10 movies ever made by Box Office Mojo. Other notable high-grossing films include Titanic ($1.8 billion), Jurassic World ($1.6 billion) and Harry Potter And The Deathly Hallows Part 2 ($1.4 billion).
+
+
+**Human**: how is cheese made? <br />
+**Assistant**: Cheese making involves the process of curdling milk, separating it into a liquid and solid phase, then heating that mixture to create a semi-solid mass. The resulting product can be either hard or soft depending on its composition. Hard cheeses are typically produced from cow's milk while softer varieties come from sheep's milk.
+
+
+**Human**: print all letters of the alphabet in reverse <br />
+**Assistant**: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
+
+
+**Human**: write a javascript function that sorts an array using quicksort algorithm <br />
+**Assistant**: 
+```
+function quicksort(array) {
+    if (array.length < 2) {
+        return array;
+    }
+    var pivot = array[0];
+    var left = quicksort(array, 0, array.length - 1);
+    var right = quicksort(array, array.length - 1, 0);
+    if (left < pivot) {
+        left = pivot;
+    }
+    if (right > pivot) {
+        right = pivot;
+    }
+    if (left < right) {
+        quicksort(array, left, right);
+    }
+```
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_lxe__Cerebras-GPT-2.7B-Alpaca-SP)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 29.4   |
+| ARC (25-shot)         | 30.8          |
+| HellaSwag (10-shot)   | 48.88    |
+| MMLU (5-shot)         | 25.12         |
+| TruthfulQA (0-shot)   | 40.24   |
+| Winogrande (5-shot)   | 55.41   |
+| GSM8K (5-shot)        | 0.53        |
+| DROP (3-shot)         | 4.78         |

config.json

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+{
+  "_name_or_path": "cerebras/Cerebras-GPT-2.7B",
+  "activation_function": "gelu",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.0,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.0,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_embd": 2560,
+  "n_head": 32,
+  "n_inner": 10240,
+  "n_layer": 32,
+  "n_positions": 2048,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.0,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.28.0.dev0",
+  "use_cache": true,
+  "vocab_size": 50257
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.28.0.dev0"
+}

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