初始化项目，由ModelHub XC社区提供模型
Model: NousResearch/Redmond-Hermes-Coder Source: Original Platform
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---
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license: gpl
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language:
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- en
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tags:
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- starcoder
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- wizardcoder
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- code
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- self-instruct
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- distillation
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---
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# Model Card: Redmond-Hermes-Coder 15B
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## Model Description
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Redmond-Hermes-Coder 15B is a state-of-the-art language model fine-tuned on over 300,000 instructions. This model was fine-tuned by Nous Research, with Teknium and Karan4D leading the fine tuning process and dataset curation, Redmond AI sponsoring the compute, and several other contributors.
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This model was trained with a WizardCoder base, which itself uses a StarCoder base model.
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The model is truly great at code, but, it does come with a tradeoff though. While far better at code than the original Nous-Hermes built on Llama, it is worse than WizardCoder at pure code benchmarks, like HumanEval.
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It comes in at 39% on HumanEval, with WizardCoder at 57%. This is a preliminary experiment, and we are exploring improvements now.
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However, it does seem better at non-code than WizardCoder on a variety of things, including writing tasks.
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## Model Training
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The model was trained almost entirely on synthetic GPT-4 outputs. This includes data from diverse sources such as GPTeacher, the general, roleplay v1&2, code instruct datasets, Nous Instruct & PDACTL (unpublished), CodeAlpaca, Evol_Instruct Uncensored, GPT4-LLM, and Unnatural Instructions.
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Additional data inputs came from Camel-AI's Biology/Physics/Chemistry and Math Datasets, Airoboros' (v1) GPT-4 Dataset, and more from CodeAlpaca. The total volume of data encompassed over 300,000 instructions.
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## Collaborators
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The model fine-tuning and the datasets were a collaboration of efforts and resources from members of Nous Research, includingTeknium, Karan4D, Huemin Art, and Redmond AI's generous compute grants.
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Huge shoutout and acknowledgement is deserved for all the dataset creators who generously share their datasets openly.
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Among the contributors of datasets, GPTeacher was made available by Teknium, Wizard LM by nlpxucan, and the Nous Research Instruct Dataset was provided by Karan4D and HueminArt.
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The GPT4-LLM and Unnatural Instructions were provided by Microsoft, Airoboros dataset by jondurbin, Camel-AI datasets are from Camel-AI, and CodeAlpaca dataset by Sahil 2801.
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If anyone was left out, please open a thread in the community tab.
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## Prompt Format
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The model follows the Alpaca prompt format:
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```
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### Instruction:
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### Response:
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```
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or
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```
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### Instruction:
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### Input:
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### Response:
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```
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## Resources for Applied Use Cases:
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For an example of a back and forth chatbot using huggingface transformers and discord, check out: https://github.com/teknium1/alpaca-discord
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For an example of a roleplaying discord bot, check out this: https://github.com/teknium1/alpaca-roleplay-discordbot
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## Future Plans
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The model is currently being uploaded in FP16 format, and there are plans to convert the model to GGML and GPTQ 4bit quantizations. The team is also working on a full benchmark, similar to what was done for GPT4-x-Vicuna. We will try to get in discussions to get the model included in the GPT4All.
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## Benchmark Results
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```
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HumanEval: 39%
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| Task |Version| Metric |Value | |Stderr|
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|------------------------------------------------|------:|---------------------|-----:|---|-----:|
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|arc_challenge | 0|acc |0.2858|± |0.0132|
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| | |acc_norm |0.3148|± |0.0136|
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|arc_easy | 0|acc |0.5349|± |0.0102|
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| | |acc_norm |0.5097|± |0.0103|
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|bigbench_causal_judgement | 0|multiple_choice_grade|0.5158|± |0.0364|
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|bigbench_date_understanding | 0|multiple_choice_grade|0.5230|± |0.0260|
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|bigbench_disambiguation_qa | 0|multiple_choice_grade|0.3295|± |0.0293|
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|bigbench_geometric_shapes | 0|multiple_choice_grade|0.1003|± |0.0159|
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| | |exact_str_match |0.0000|± |0.0000|
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|bigbench_logical_deduction_five_objects | 0|multiple_choice_grade|0.2260|± |0.0187|
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|bigbench_logical_deduction_seven_objects | 0|multiple_choice_grade|0.1957|± |0.0150|
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|bigbench_logical_deduction_three_objects | 0|multiple_choice_grade|0.3733|± |0.0280|
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|bigbench_movie_recommendation | 0|multiple_choice_grade|0.3200|± |0.0209|
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|bigbench_navigate | 0|multiple_choice_grade|0.4830|± |0.0158|
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|bigbench_reasoning_about_colored_objects | 0|multiple_choice_grade|0.4150|± |0.0110|
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|bigbench_ruin_names | 0|multiple_choice_grade|0.2143|± |0.0194|
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|bigbench_salient_translation_error_detection | 0|multiple_choice_grade|0.2926|± |0.0144|
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|bigbench_snarks | 0|multiple_choice_grade|0.5249|± |0.0372|
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|bigbench_sports_understanding | 0|multiple_choice_grade|0.4817|± |0.0159|
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|bigbench_temporal_sequences | 0|multiple_choice_grade|0.2700|± |0.0140|
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|bigbench_tracking_shuffled_objects_five_objects | 0|multiple_choice_grade|0.1864|± |0.0110|
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|bigbench_tracking_shuffled_objects_seven_objects| 0|multiple_choice_grade|0.1349|± |0.0082|
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|bigbench_tracking_shuffled_objects_three_objects| 0|multiple_choice_grade|0.3733|± |0.0280|
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|boolq | 1|acc |0.5498|± |0.0087|
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|hellaswag | 0|acc |0.3814|± |0.0048|
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| | |acc_norm |0.4677|± |0.0050|
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|openbookqa | 0|acc |0.1960|± |0.0178|
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| | |acc_norm |0.3100|± |0.0207|
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|piqa | 0|acc |0.6600|± |0.0111|
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| | |acc_norm |0.6610|± |0.0110|
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|winogrande | 0|acc |0.5343|± |0.0140|
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```
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## Model Usage
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The model is available for download on Hugging Face. It is suitable for a wide range of language tasks, from generating creative text to understanding and following complex instructions.
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Compute provided by our project sponsor Redmond AI, thank you!!
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"_name_or_path": "./hermeswizardcoder-step3800/",
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"activation_function": "gelu",
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"architectures": [
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"GPTBigCodeForCausalLM"
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],
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"model_type": "gpt_bigcode",
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"multi_query": true,
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"n_embd": 6144,
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"n_head": 48,
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"n_inner": 24576,
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"n_layer": 40,
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"n_positions": 8192,
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"pad_key_length": true,
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"pre_allocate_kv_cache": false,
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"resid_pdrop": 0.1,
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"scale_attention_softmax_in_fp32": true,
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"scale_attn_weights": true,
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"summary_proj_to_labels": true,
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"use_cache": false,
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"validate_runner_input": true,
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"vocab_size": 49153
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}
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||||||
|
"transformer.h.37.mlp.c_proj.bias": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.37.mlp.c_proj.weight": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.attn.c_attn.bias": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.attn.c_attn.weight": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.attn.c_proj.bias": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.attn.c_proj.weight": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.ln_1.bias": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.ln_1.weight": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.ln_2.bias": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.ln_2.weight": "pytorch_model-00003-of-00004.bin",
|
||||||
|
"transformer.h.38.mlp.c_fc.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.38.mlp.c_fc.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.38.mlp.c_proj.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.38.mlp.c_proj.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.attn.c_attn.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.attn.c_attn.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.attn.c_proj.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.attn.c_proj.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.ln_1.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.ln_1.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.ln_2.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.ln_2.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.mlp.c_fc.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.mlp.c_fc.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.mlp.c_proj.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.39.mlp.c_proj.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.h.4.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.ln_1.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.ln_1.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.ln_2.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.ln_2.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.4.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.ln_1.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.ln_1.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.ln_2.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.ln_2.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.5.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.ln_1.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.ln_1.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.ln_2.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.ln_2.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.6.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.ln_1.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.ln_1.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.ln_2.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.ln_2.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.7.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.ln_1.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.ln_1.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.ln_2.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.ln_2.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.8.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.attn.c_attn.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.attn.c_attn.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.attn.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.attn.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.ln_1.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.ln_1.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.ln_2.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.ln_2.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.mlp.c_fc.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.mlp.c_fc.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.mlp.c_proj.bias": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.h.9.mlp.c_proj.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.ln_f.bias": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.ln_f.weight": "pytorch_model-00004-of-00004.bin",
|
||||||
|
"transformer.wpe.weight": "pytorch_model-00001-of-00004.bin",
|
||||||
|
"transformer.wte.weight": "pytorch_model-00001-of-00004.bin"
|
||||||
|
}
|
||||||
|
}
|
||||||
27
special_tokens_map.json
Normal file
27
special_tokens_map.json
Normal file
@@ -0,0 +1,27 @@
|
|||||||
|
{
|
||||||
|
"additional_special_tokens": [
|
||||||
|
"<|endoftext|>",
|
||||||
|
"<fim_prefix>",
|
||||||
|
"<fim_middle>",
|
||||||
|
"<fim_suffix>",
|
||||||
|
"<fim_pad>",
|
||||||
|
"<filename>",
|
||||||
|
"<gh_stars>",
|
||||||
|
"<issue_start>",
|
||||||
|
"<issue_comment>",
|
||||||
|
"<issue_closed>",
|
||||||
|
"<jupyter_start>",
|
||||||
|
"<jupyter_text>",
|
||||||
|
"<jupyter_code>",
|
||||||
|
"<jupyter_output>",
|
||||||
|
"<empty_output>",
|
||||||
|
"<commit_before>",
|
||||||
|
"<commit_msg>",
|
||||||
|
"<commit_after>",
|
||||||
|
"<reponame>"
|
||||||
|
],
|
||||||
|
"bos_token": "<|endoftext|>",
|
||||||
|
"eos_token": "<|endoftext|>",
|
||||||
|
"pad_token": "[PAD]",
|
||||||
|
"unk_token": "<|endoftext|>"
|
||||||
|
}
|
||||||
98266
tokenizer.json
Normal file
98266
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
32
tokenizer_config.json
Normal file
32
tokenizer_config.json
Normal file
@@ -0,0 +1,32 @@
|
|||||||
|
{
|
||||||
|
"add_prefix_space": false,
|
||||||
|
"additional_special_tokens": [
|
||||||
|
"<|endoftext|>",
|
||||||
|
"<fim_prefix>",
|
||||||
|
"<fim_middle>",
|
||||||
|
"<fim_suffix>",
|
||||||
|
"<fim_pad>",
|
||||||
|
"<filename>",
|
||||||
|
"<gh_stars>",
|
||||||
|
"<issue_start>",
|
||||||
|
"<issue_comment>",
|
||||||
|
"<issue_closed>",
|
||||||
|
"<jupyter_start>",
|
||||||
|
"<jupyter_text>",
|
||||||
|
"<jupyter_code>",
|
||||||
|
"<jupyter_output>",
|
||||||
|
"<empty_output>",
|
||||||
|
"<commit_before>",
|
||||||
|
"<commit_msg>",
|
||||||
|
"<commit_after>",
|
||||||
|
"<reponame>"
|
||||||
|
],
|
||||||
|
"bos_token": "<|endoftext|>",
|
||||||
|
"clean_up_tokenization_spaces": true,
|
||||||
|
"eos_token": "<|endoftext|>",
|
||||||
|
"model_max_length": 2048,
|
||||||
|
"padding_side": "right",
|
||||||
|
"tokenizer_class": "GPT2Tokenizer",
|
||||||
|
"unk_token": "<|endoftext|>",
|
||||||
|
"vocab_size": 49152
|
||||||
|
}
|
||||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user