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license: apache-2.0 |
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--- |
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A full SFT of original 'ibm-granitte/granitte-8b-code-instruct' using a mix of English and Serbian instruction data. |
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Usage: |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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device = "cuda" # or "cpu" |
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model_path = "cminja/granitte-8b-code-instruct" |
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tokenizer = AutoTokenizer.from_pretrained(model_path) |
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# drop device_map if running on CPU |
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model = AutoModelForCausalLM.from_pretrained(model_path, device_map=device) |
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model.eval() |
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# change input text as desired |
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chat = [ |
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{ "role": "user", "content": "Write a code to find the maximum value in a list of numbers." }, |
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] |
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chat = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True) |
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# tokenize the text |
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input_tokens = tokenizer(chat, return_tensors="pt") |
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# transfer tokenized inputs to the device |
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for i in input_tokens: |
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input_tokens[i] = input_tokens[i].to(device) |
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# generate output tokens |
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output = model.generate(**input_tokens, max_new_tokens=100) |
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# decode output tokens into text |
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output = tokenizer.batch_decode(output) |
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# loop over the batch to print, in this example the batch size is 1 |
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for i in output: |
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print(i) |
