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--- |
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license: cc-by-nc-2.0 |
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language: |
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- en |
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- pt |
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tags: |
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- classification |
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- llama |
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- tinyllama |
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- rag |
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- rerank |
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--- |
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```python |
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template = """<s><|system|> |
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You are a chatbot who always responds in JSON format indicating if the context contains relevant information to answer the question</s> |
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<|user|> |
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Context: |
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{Text} |
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Question: |
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{Prompt}</s> |
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<|assistant|> |
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""" |
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# Output should be: |
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{"relevant": true} |
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# or |
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{"relevant": false} |
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``` |
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Example: |
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```text |
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<s><|system|> |
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You are a chatbot who always responds in JSON format indicating if the context contains relevant information to answer the question</s> |
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<|user|> |
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Context: |
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old. NFT were observed in almost all patients over 60 years of age, but the incidence was low. |
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Many ubiquitin-positive small-sized granules were observed in the second and third layer of the parahippocampal gyrus of aged patients, |
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and the incidence rose with increasing age. On the other hand, few of these granules were in patients with Alzheimer\'s type dementia. |
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Granulovacuolar degeneration was examined. Many centrally-located granules were positive for ubiquitin. Based on electron microscopic |
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observation of these granules at several stages, the granules were thought to be a type of autophagosome. During the first stage of |
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granulovacuolar degeneration, electron-dense materials appeared in the cytoplasm, following which they were surrounded by smooth cytoplasm, |
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following which they were surrounded by smooth endoplasmic reticulum. Analytical electron microscopy disclosed that the granules contained |
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some aluminium. Several senile changes in the central nervous system in cadavers were examined. The pattern of extension of Alzheimer\'s |
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neurofibrillary tangles (NFT) and senile plaques (SP) in the olfactory bulbs of 100 specimens was examined during routine autopsy by |
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immunohistochemical staining. NFT were first observed in the anterior olfactory nucleus after the age of 60, and incidence rose with |
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increasing age. Senile plaques were found in the nucleus when there were many SP in the cerebral cortex. Of 25 non-demented amyotrophic |
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lateral sclerosis patients, SP were found in the cerebral cortices of 10, and 9 of 10 were over 60 years old. NFT were observed in almost |
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all patients over |
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Question: |
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What is granulovacuolar degeneration and what was its observation on electron microscopy?</s> |
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<|assistant|> |
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{"relevant": true}</s> |
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``` |
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vLLM recommended request parameters: |
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```python |
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prompt = "<s><|system|>\nYou are a chatbot who always responds in JSON format indicating if the context contains relevant information to answer the question</s>\n<|user|>\nContext:\nConhecida como missão de imagem de raios-x e espectroscopia (da sigla em inglês XRISM), a estratégia é utilizar o telescópio para ampliar os estudos da humanidade a níveis celestiais com uma fração dos pixels da tela de um Gameboy original, lançado em 1989. Isso é possível por meio de uma ferramenta chamada “Resolve”. Apesar de utilizar a medição em pixels, a tecnologia é bastante diferente de uma câmera. Com um conjunto de microcalorímetros de seis pixels quadrados que mede 0,5 cm², ela detecta a temperatura de cada raio-x que o atinge. Como funciona o Resolve do telescópio XRISM? Cientista do projeto XRISM da NASA, Brian Williams explicou em um comunicado o funcionamento do telescópio. “Chamamos o Resolve de espectrômetro de microcalorímetros porque cada um de seus 36 pixels está medindo pequenas quantidades de calor entregues por cada raio-x recebido, nos permitindo ver as impressões digitais químicas dos elementos que compõem as fontes com detalhes sem precedentes”.\n\nQuestion:\nQual é a sigla em alemão mencionada?</s>\n<|assistant|>\n{\"relevant\":" |
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headers = { |
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"Accept": "text/event-stream", |
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"Authorization": "Bearer EMPTY" |
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} |
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body = { |
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"model": model, |
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"prompt": [prompt], |
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"best_of": 5, |
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"max_tokens": 1, |
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"temperature": 0, |
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"top_p": 1, |
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"use_beam_search": True, |
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"top_k": -1, |
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"min_p": 0, |
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"repetition_penalty": 1, |
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"length_penalty": 1, |
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"min_tokens": 1, |
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"logprobs": 1 |
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} |
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result = requests.post(base_uri, headers=headers, json=body) |
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result = result.json() |
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boolean_response = bool(eval(json_result['choices'][0]['text'].strip().title())) |
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print(boolean_response) |
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``` |