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Model: rasyosef/Mistral-NeMo-Minitron-8B-Chat
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README.md

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+---
+license: other
+library_name: transformers
+base_model: nvidia/Mistral-NeMo-Minitron-8B-Base
+datasets:
+- teknium/OpenHermes-2.5
+pipeline_tag: text-generation
+license_name: nvidia-open-model-license
+license_link: https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
+model-index:
+- name: Mistral-NeMo-Minitron-8B-Chat
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 44.52
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=rasyosef/Mistral-NeMo-Minitron-8B-Chat
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 26.04
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=rasyosef/Mistral-NeMo-Minitron-8B-Chat
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 0.76
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=rasyosef/Mistral-NeMo-Minitron-8B-Chat
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 3.47
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=rasyosef/Mistral-NeMo-Minitron-8B-Chat
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 12.94
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=rasyosef/Mistral-NeMo-Minitron-8B-Chat
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 15.6
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=rasyosef/Mistral-NeMo-Minitron-8B-Chat
+      name: Open LLM Leaderboard
+---
+
+# Mistral-NeMo-Minitron-8B-Chat
+
+This is an instruction-tuned version of [nvidia/Mistral-NeMo-Minitron-8B-Base](https://huggingface.co/nvidia/Mistral-NeMo-Minitron-8B-Base) that has underwent **supervised fine-tuning** with 32k instruction-response pairs from the [teknium/OpenHermes-2.5](https://huggingface.co/datasets/teknium/OpenHermes-2.5) dataset.
+
+## How to use
+### Chat Format
+
+Given the nature of the training data, the Mistral-NeMo-Minitron-8B chat model is best suited for prompts using the chat format as follows. 
+You can provide the prompt as a question with a generic template as follows:
+```markdown
+<|im_start|>system
+You are a helpful assistant.<|im_end|>
+<|im_start|>user
+Question?<|im_end|>
+<|im_start|>assistant
+```
+
+For example:
+```markdown
+<|im_start|>system
+You are a helpful assistant.<|im_end|>
+<|im_start|>user
+How to explain Internet for a medieval knight?<|im_end|>
+<|im_start|>assistant
+```
+where the model generates the text after `<|im_start|>assistant` .
+
+### Sample inference code
+
+This code snippets show how to get quickly started with running the model on a GPU:
+
+```python
+import torch 
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline 
+
+torch.random.manual_seed(0) 
+
+model_id = "rasyosef/Mistral-NeMo-Minitron-8B-Chat"
+model = AutoModelForCausalLM.from_pretrained( 
+    model_id,  
+    device_map="auto",  
+    torch_dtype=torch.bfloat16 
+) 
+
+tokenizer = AutoTokenizer.from_pretrained(model_id) 
+
+messages = [ 
+    {"role": "system", "content": "You are a helpful AI assistant."}, 
+    {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"}, 
+    {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."}, 
+    {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"}, 
+] 
+
+pipe = pipeline( 
+    "text-generation", 
+    model=model, 
+    tokenizer=tokenizer, 
+) 
+
+generation_args = { 
+    "max_new_tokens": 256, 
+    "return_full_text": False, 
+    "temperature": 0.0, 
+    "do_sample": False, 
+} 
+
+output = pipe(messages, **generation_args) 
+print(output[0]['generated_text'])  
+```
+
+Note: If you want to use flash attention, call _AutoModelForCausalLM.from_pretrained()_ with _attn_implementation="flash_attention_2"_
+
+
+## Benchmarks
+
+These benchmarks were run using EleutherAI's [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)
+
+- **IFEval (Instruction Following Evaluation)**: IFEval is a fairly interesting dataset that tests the capability of models to clearly follow explicit instructions, such as “include keyword x” or “use format y”. The models are tested on their ability to strictly follow formatting instructions rather than the actual contents generated, allowing strict and rigorous metrics to be used.
+  - Score: **45.83**
+
+## Demo
+
+Here's a colab notebook with a chat interface, you can use this to interact with the chat model.
+
+https://huggingface.co/rasyosef/Mistral-NeMo-Minitron-8B-Chat/blob/main/Mistral_NeMo_Minitron_8B_chatbot.ipynb
+
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_rasyosef__Mistral-NeMo-Minitron-8B-Chat)
+
+|      Metric       |Value|
+|-------------------|----:|
+|Avg.               |17.22|
+|IFEval (0-Shot)    |44.52|
+|BBH (3-Shot)       |26.04|
+|MATH Lvl 5 (4-Shot)| 0.76|
+|GPQA (0-shot)      | 3.47|
+|MuSR (0-shot)      |12.94|
+|MMLU-PRO (5-shot)  |15.60|
+

config.json

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+{
+  "_name_or_path": "nvidia/Mistral-NeMo-Minitron-8B-Base",
+  "activation": "silu",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 131072,
+  "eos_token_id": 131073,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11520,
+  "max_position_embeddings": 8192,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "pad_token_id": 131073,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 131074
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 131072,
+  "eos_token_id": 131073,
+  "pad_token_id": 131073,
+  "transformers_version": "4.44.2"
+}

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+}

special_tokens_map.json

@@ -0,0 +1,28 @@
+{
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+    {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false
+    },
+    {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false
+    }
+  ],
+  "bos_token": "<|im_start|>",
+  "eos_token": "<|im_end|>",
+  "pad_token": "<|im_end|>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}