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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1hape to make2 it 2-D. The shape of the result will be c.shape[2:] + x.shape.3 4 Parameters5 ----------6 x, y : array_like, compatible objects7 The two dimensional series is evaluated at the points `(x, y)`,8 where `x` and `y` must have the same shape. If `x` or `y` is a list9 or tuple, it is first converted to an ndarray, otherwise it is left10 unchanged and if it isn't an ndarray it is treated as a scalar.11 c : array_like12 Array of coefficients ordered so that the coefficient of the term13 of multi-degree i,j is contained in ``c[i,j]``. If `c` has14 dimension greater than two the remaining indices enumerate multiple15 sets of coefficients.16 17 Returns18 -------19 values : ndarray, compatible object20 The values of the two dimensional Legendre series at points formed21 from pairs of corresponding values from `x` and `y`.22 23 See Also24 --------25 legval, leggrid2d, legval3d, leggrid3d26 27 Notes28 -----29 30 .. versionadded:: 1.7.031 32 """33 return pu._valnd(legval, c, x, y)