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Model: rasyosef/Llama-3.1-Minitron-4B-Chat Source: Original Platform
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README.md
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---
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library_name: transformers
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base_model: nvidia/Llama-3.1-Minitron-4B-Width-Base
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datasets:
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- teknium/OpenHermes-2.5
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pipeline_tag: text-generation
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license: other
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license_name: nvidia-open-model-license
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license_link: >-
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https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
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---
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# Llama-3.1-Minitron-4B-Chat
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This is an instruction-tuned version of [nvidia/Llama-3.1-Minitron-4B-Width-Base](https://huggingface.co/nvidia/Llama-3.1-Minitron-4B-Width-Base) that has underwent **supervised fine-tuning** with 64k instruction-response pairs from the [teknium/OpenHermes-2.5](https://huggingface.co/datasets/teknium/OpenHermes-2.5) dataset on a single **A100 40GB** GPU.
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## How to use
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### Chat Format
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Given the nature of the training data, the Llama-3.1-Minitron-4B chat model is best suited for prompts using the chat format as follows.
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You can provide the prompt as a question with a generic template as follows:
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```markdown
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<|im_start|>system
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You are a helpful assistant.<|im_end|>
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<|im_start|>user
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Question?<|im_end|>
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<|im_start|>assistant
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```
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For example:
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```markdown
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<|im_start|>system
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You are a helpful assistant.<|im_end|>
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<|im_start|>user
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How to explain Internet for a medieval knight?<|im_end|>
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<|im_start|>assistant
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```
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where the model generates the text after `<|im_start|>assistant` .
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### Sample inference code
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Support for this model will be added in the upcoming transformers release. In the meantime, please **install the library from source**:
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```
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pip install git+https://github.com/huggingface/transformers
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```
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This code snippets show how to get quickly started with running the model on a GPU:
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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torch.random.manual_seed(0)
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model_id = "rasyosef/Llama-3.1-Minitron-4B-Chat"
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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device_map="auto",
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torch_dtype=torch.bfloat16
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)
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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messages = [
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{"role": "system", "content": "You are a helpful AI assistant."},
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{"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
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{"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."},
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{"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
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]
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pipe = pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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)
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generation_args = {
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"max_new_tokens": 256,
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"return_full_text": False,
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"temperature": 0.0,
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"do_sample": False,
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}
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output = pipe(messages, **generation_args)
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print(output[0]['generated_text'])
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```
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Note: If you want to use flash attention, call _AutoModelForCausalLM.from_pretrained()_ with _attn_implementation="flash_attention_2"_
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config.json
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config.json
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{
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"_name_or_path": "nvidia/Llama-3.1-Minitron-4B-Width-Base",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128256,
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"eos_token_id": 128257,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 9216,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.45.0.dev0",
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"use_cache": true,
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"vocab_size": 128258
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}
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generation_config.json
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21
special_tokens_map.json
Normal file
21
special_tokens_map.json
Normal file
@@ -0,0 +1,21 @@
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"eos_token": "<|im_end|>",
|
||||
"pad_token": "<|im_end|>"
|
||||
}
|
||||
410581
tokenizer.json
Normal file
410581
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2083
tokenizer_config.json
Normal file
2083
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user