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--- |
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base_model: "meta-llama/Meta-Llama-3-8B-Instruct" |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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- facebook |
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- meta |
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- pytorch |
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- llama |
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- llama-3 |
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language: |
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- en |
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pipeline_tag: text-generation |
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license: other |
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license_name: llama3 |
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license_link: LICENSE |
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inference: false |
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model_creator: MaziyarPanahi |
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model_name: Llama-3-13B-Instruct-v0.1 |
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quantized_by: MaziyarPanahi |
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--- |
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<img src="./llama-3-merges.webp" alt="Goku 8x22B v0.1 Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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# Llama-3-13B-Instruct-v0.1 |
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This model is a self-merge of `meta-llama/Meta-Llama-3-8B-Instruct` model. |
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# How to use |
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You can use this model by using `MaziyarPanahi/Llama-3-13B-Instruct-v0.1` as the model name in Hugging Face's |
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transformers library. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer |
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from transformers import pipeline |
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import torch |
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model_id = "MaziyarPanahi/Llama-3-13B-Instruct-v0.1" |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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torch_dtype=torch.float16, |
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device_map="auto", |
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trust_remote_code=True, |
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# attn_implementation="flash_attention_2" |
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) |
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tokenizer = AutoTokenizer.from_pretrained( |
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model_id, |
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trust_remote_code=True |
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) |
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streamer = TextStreamer(tokenizer) |
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pipeline = pipeline( |
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"text-generation", |
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model=model, |
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tokenizer=tokenizer, |
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model_kwargs={"torch_dtype": torch.bfloat16}, |
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streamer=streamer |
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) |
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# Then you can use the pipeline to generate text. |
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messages = [ |
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{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"}, |
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{"role": "user", "content": "Who are you?"}, |
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] |
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prompt = tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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) |
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terminators = [ |
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tokenizer.eos_token_id, |
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tokenizer.convert_tokens_to_ids("<|eot_id|>") |
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] |
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outputs = pipeline( |
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prompt, |
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max_new_tokens=256, |
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eos_token_id=terminators, |
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do_sample=True, |
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temperature=0.6, |
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top_p=0.95, |
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) |
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print(outputs[0]["generated_text"][len(prompt):]) |
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``` |
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## Prompt template |
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```text |
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<|begin_of_text|><|start_header_id|>system<|end_header_id|> |
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You are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|> |
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what's 25-4*2+3<|eot_id|><|start_header_id|>assistant<|end_header_id|> |
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To evaluate this expression, we need to follow the order of operations (PEMDAS): |
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1. First, multiply 4 and 2: 4*2 = 8 |
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2. Then, subtract 8 from 25: 25 - 8 = 17 |
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3. Finally, add 3: 17 + 3 = 20 |
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So, 25-4*2+3 = 20!<|eot_id|> |
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To evaluate this expression, we need to follow the order of operations (PEMDAS): |
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|
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1. First, multiply 4 and 2: 4*2 = 8 |
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2. Then, subtract 8 from 25: 25 - 8 = 17 |
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3. Finally, add 3: 17 + 3 = 20 |
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So, 25-4*2+3 = 20! |
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``` |
