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--- |
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language: |
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- en |
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license: other |
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library_name: transformers |
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tags: |
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- axolotl |
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- finetune |
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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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base_model: MaziyarPanahi/Llama-3-8B-Instruct-v0.8 |
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model_name: Llama-3-8B-Instruct-v0.9 |
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pipeline_tag: text-generation |
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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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quantized_by: MaziyarPanahi |
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model-index: |
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- name: Llama-3-8B-Instruct-v0.9 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 72.35 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-v0.9 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 88.17 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-v0.9 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 68.1 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-v0.9 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 64.67 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-v0.9 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 79.95 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-v0.9 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 66.49 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=MaziyarPanahi/Llama-3-8B-Instruct-v0.9 |
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name: Open LLM Leaderboard |
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--- |
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<img src="./llama-3-merges.webp" alt="Llama-3 DPO Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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# Llama-3-8B-Instruct-v0.9 |
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This model was developed based on `MaziyarPanahi/Llama-3-8B-Instruct-v0.8` model. |
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# ⚡ Quantized GGUF |
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All GGUF models are available here: [MaziyarPanahi/Llama-3-8B-Instruct-v0.9-GGUF](https://huggingface.co/MaziyarPanahi/Llama-3-8B-Instruct-v0.9-GGUF) |
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# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__Llama-3-8B-Instruct-v0.9) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |73.29| |
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|AI2 Reasoning Challenge (25-Shot)|72.35| |
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|HellaSwag (10-Shot) |88.17| |
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|MMLU (5-Shot) |68.10| |
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|TruthfulQA (0-shot) |64.67| |
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|Winogrande (5-shot) |79.95| |
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|GSM8k (5-shot) |66.49| |
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`MaziyarPanahi/Llama-3-8B-Instruct-v0.9` is the 4th best-performing 8B model on the Open LLM Leaderboard. (03/06/2024). |
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# Prompt Template |
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This model uses `ChatML` prompt template: |
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``` |
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<|begin_of_text|><|start_header_id|>system<|end_header_id|> |
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{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|> |
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{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|> |
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```` |
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# How to use |
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You can use this model by using `MaziyarPanahi/Llama-3-8B-Instruct-v0.9` 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-3-8B-Instruct-v0.9" |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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torch_dtype=torch.bfloat16, |
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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=512, |
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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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