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--- |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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This model is finetuend on "mistralai/Mixtral-8x7B-v0.1" with Firefly |
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## Run the model |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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model_name_or_path = 'YeungNLP/firefly-mixtral-8x7b' |
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max_new_tokens = 500 |
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top_p = 0.9 |
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temperature = 0.35 |
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repetition_penalty = 1.0 |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name_or_path, |
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trust_remote_code=True, |
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low_cpu_mem_usage=True, |
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torch_dtype=torch.float16, |
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device_map='auto' |
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) |
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model = model.eval() |
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tokenizer = AutoTokenizer.from_pretrained(model_name_or_path) |
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text = "Compose an engaging travel blog post about a recent trip to Hawaii, highlighting cultural experiences and must-see attractions." |
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inst_begin_tokens = tokenizer.encode('[INST]', add_special_tokens=False) |
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inst_end_tokens = tokenizer.encode('[/INST]', add_special_tokens=False) |
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human_tokens = tokenizer.encode(text, add_special_tokens=False) |
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input_ids = [tokenizer.bos_token_id] + inst_begin_tokens + human_tokens + inst_end_tokens |
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# input_ids = human_tokens |
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input_ids = torch.tensor([input_ids], dtype=torch.long).cuda() |
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with torch.no_grad(): |
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outputs = model.generate( |
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input_ids=input_ids, max_new_tokens=max_new_tokens, do_sample=True, |
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top_p=top_p, temperature=temperature, repetition_penalty=repetition_penalty, |
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eos_token_id=tokenizer.eos_token_id |
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) |
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outputs = outputs.tolist()[0][len(input_ids[0]):] |
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response = tokenizer.decode(outputs) |
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response = response.strip().replace(tokenizer.eos_token, "").strip() |
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print("Chatbot:{}".format(response)) |
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``` |
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