23ws-LLMcoder/LLMcoder-GitHub-Python-Mix-Direct
Dataset Card for LLMcoder-GitHub-Python-Mix-Direct Python target autocomplete suggestions in the format of conversations for OpenAI's fine-tuning. Dataset Details Dataset Description Curated by: [More Information Needed] Funded by [optional]: [More Information Needed] Shared by [optional]: [More Information Needed] Language(s) (NLP): [More Information Needed] License: [More Information Needed] Dataset Sources [optional] The data… See the full description on the dataset page: https://huggingface.co/datasets/23ws-LLMcoder/LLMcoder-GitHub-Python-Mix-Direct.
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1temperature=0.122 )3 >>>4 >>> # complete the prompt5 >>> result = client.complete(request, model=model_name)6 """7 response = self._post_request("complete", request, model)8 return CompletionResponse.from_json(response)9 10 def tokenize(11 self,12 request: TokenizationRequest,13 model: str,14 ) -> TokenizationResponse:15 """Tokenizes the given prompt for the given model.16 17 Parameters:18 request (TokenizationRequest, required):19 Parameters for the requested tokenization.20 21 model (string, required):22 Name of model to use. A model name refers to a model architecture (number of parameters among others).23 Always the latest version of model is used.24 25 Examples:26 >>> request = TokenizationRequest(27 prompt="hello", token_ids=True, tokens=True28 )29 >>> response = client.tokenize(request, model=model_name)30 """31 response = self._post_request(32 "tokenize",33 request,34 model,35 )36 return TokenizationResponse.from_json(response)37 38 def detokenize(39 self,40 request: DetokenizationRequest,41 model: str,42 ) -> DetokenizationResponse:43 """Detokenizes the given prompt for the given model.44 45 Parameters:46 request (DetokenizationRequest, required):47 Parameters for the requested detokenization.48 49 model (string, required):50 Name of model to use. A model name refers to a model architecture (number of parameters among others).51 Always the latest version of model is used.52 53 Examples:54 >>> request = DetokenizationRequest(token_ids=[2, 3, 4])55 >>> response = client.detokenize(request, model=model_name)56 """57 response = sel