rasyosef
/

Mistral-NeMo-Minitron-8B-Chat

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 ---
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 ---
 library_name: transformers
+base_model: nvidia/Mistral-NeMo-Minitron-8B-Base
+datasets:
+- teknium/OpenHermes-2.5
+pipeline_tag: text-generation
+license: other
+license_name: nvidia-open-model-license
+license_link: >-
+  https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
 ---
+# 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 phi-2 instruct 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"_