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Model: Sharathhebbar24/convo_bot_gpt_v1
Source: Original Platform

README.md

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+---
+language:
+- en
+license: apache-2.0
+datasets:
+- vicgalle/alpaca-gpt4
+metrics:
+- perplexity
+pipeline_tag: text-generation
+model-index:
+- name: convo_bot_gpt_v1
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 22.35
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Sharathhebbar24/convo_bot_gpt_v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 31.07
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Sharathhebbar24/convo_bot_gpt_v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 26.12
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Sharathhebbar24/convo_bot_gpt_v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 38.71
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Sharathhebbar24/convo_bot_gpt_v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 51.54
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Sharathhebbar24/convo_bot_gpt_v1
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 0.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Sharathhebbar24/convo_bot_gpt_v1
+      name: Open LLM Leaderboard
+---
+
+
+This model is a finetuned version of ```gpt2``` using ```vicgalle/alpaca-gpt4```
+
+## Model description
+
+GPT-2 is a transformers model pre-trained on a very large corpus of English data in a self-supervised fashion. This
+means it was pre-trained on the raw texts only, with no humans labeling them in any way (which is why it can use lots
+of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely,
+it was trained to guess the next word in sentences.
+
+More precisely, inputs are sequences of continuous text of a certain length and the targets are the same sequence,
+shifting one token (word or piece of word) to the right. The model uses a masking mechanism to make sure the
+predictions for the token `i` only use the inputs from `1` to `i` but not the future tokens.
+
+This way, the model learns an inner representation of the English language that can then be used to extract features
+useful for downstream tasks. The model is best at what it was trained for, however, which is generating texts from a
+prompt.
+
+### To use this model
+
+```python
+>>> from transformers import AutoTokenizer, AutoModelForCausalLM
+>>> model_name = "Sharathhebbar24/convo_bot_gpt2"
+>>> model = AutoModelForCausalLM.from_pretrained(model_name)
+>>> tokenizer = AutoTokenizer.from_pretrained("gpt2")
+>>> def generate_text(prompt):
+>>>  inputs = tokenizer.encode(prompt, return_tensors='pt')
+>>>  outputs = mod1.generate(inputs, max_length=64, pad_token_id=tokenizer.eos_token_id)
+>>>  generated = tokenizer.decode(outputs[0], skip_special_tokens=True)
+>>>  return generated
+>>>  prompt = """
+>>>  Below is an instruction that describes a task. Write a response that appropriately completes the request. 
+>>>  ### Instruction: Who is the world's most famous painter? 
+>>>  ###
+>>>  """
+>>> res = generate_text(prompt)
+>>> res
+```
+# [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_Sharathhebbar24__convo_bot_gpt_v1)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |28.30|
+|AI2 Reasoning Challenge (25-Shot)|22.35|
+|HellaSwag (10-Shot)              |31.07|
+|MMLU (5-Shot)                    |26.12|
+|TruthfulQA (0-shot)              |38.71|
+|Winogrande (5-shot)              |51.54|
+|GSM8k (5-shot)                   | 0.00|
+