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Model: ibm-research/PowerLM-3b Source: Original Platform
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README.md
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---
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pipeline_tag: text-generation
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inference: false
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license: apache-2.0
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library_name: transformers
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model-index:
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- name: ibm/PowerLM-3b
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results:
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: ARC
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metrics:
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- name: accuracy-norm
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type: accuracy-norm
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value: 60.5
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verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: BoolQ
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metrics:
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- name: accuracy
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type: accuracy
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value: 72.0
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verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: Hellaswag
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metrics:
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- name: accuracy-norm
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type: accuracy-norm
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value: 74.6
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verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: OpenBookQA
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metrics:
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||||
- name: accuracy-norm
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type: accuracy-norm
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value: 43.6
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||||
verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: PIQA
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metrics:
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- name: accuracy-norm
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type: accuracy-norm
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value: 79.9
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verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: Winogrande
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metrics:
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- name: accuracy-norm
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type: accuracy-norm
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value: 70.0
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verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: MMLU (5 shot)
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metrics:
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- name: accuracy
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type: accuracy
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value: 49.2
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verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: GSM8k (5 shot)
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metrics:
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- name: accuracy
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type: accuracy
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value: 34.9
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verified: false
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- task:
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type: text-generation
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dataset:
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type: lm-eval-harness
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name: math (4 shot)
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metrics:
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- name: accuracy
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||||
type: accuracy
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value: 15.2
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verified: false
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- task:
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type: text-generation
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dataset:
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type: bigcode-eval
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name: humaneval
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metrics:
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- name: pass@1
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type: pass@1
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value: 26.8
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verified: false
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- task:
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type: text-generation
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dataset:
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type: bigcode-eval
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name: MBPP
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metrics:
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- name: pass@1
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type: pass@1
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value: 33.6
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verified: false
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---
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## Model Summary
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PowerLM-3B is a 3B state-of-the-art small language model trained with the Power learning rate scheduler. It is trained on a mix of open-source and proprietary datasets. PowerLM-3B has shown promising results compared to other models in the size categories across various benchmarks, including natural language multi-choices, code generation, and math reasoning.
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Paper: https://arxiv.org/abs/2408.13359
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## Usage
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Note: Requires installing HF transformers from source.
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### Generation
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This is a simple example of how to use **PowerLM-3b** model.
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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device = "cuda" # or "cpu"
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model_path = "ibm/PowerLM-3b"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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# drop device_map if running on CPU
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model = AutoModelForCausalLM.from_pretrained(model_path, device_map=device)
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model.eval()
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# change input text as desired
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prompt = "Write a code to find the maximum value in a list of numbers."
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# tokenize the text
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input_tokens = tokenizer(prompt, return_tensors="pt")
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# transfer tokenized inputs to the device
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for i in input_tokens:
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input_tokens[i] = input_tokens[i].to(device)
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# generate output tokens
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output = model.generate(**input_tokens, max_new_tokens=100)
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# decode output tokens into text
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output = tokenizer.batch_decode(output)
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# loop over the batch to print, in this example the batch size is 1
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for i in output:
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print(i)
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```
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config.json
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"GraniteForCausalLM"
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"attention_dropout": 0.1,
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"attention_multiplier": 0.015625,
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"bos_token_id": 0,
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"embedding_multiplier": 12.0,
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"hidden_act": "silu",
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"hidden_size": 2304,
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"initializer_range": 0.02,
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"intermediate_size": 9216,
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"logits_scaling": 9.0,
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"max_position_embeddings": 4096,
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"mlp_bias": true,
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"model_type": "granite",
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"num_attention_heads": 36,
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"num_hidden_layers": 40,
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"num_key_value_heads": 36,
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"pad_token_id": 0,
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"residual_multiplier": 0.22,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000,
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"tie_word_embeddings": true,
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"transformers_version": "4.45.0.dev0",
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"use_cache": true,
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"vocab_size": 49152
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}
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51
special_tokens_map.json
Normal file
51
special_tokens_map.json
Normal file
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"unk_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d3b4df07a0ce3940b15c77e2ea17ab5627ca0c4bf982d2eb37966aea0a81c918
|
||||
size 2057451
|
||||
187
tokenizer_config.json
Normal file
187
tokenizer_config.json
Normal file
@@ -0,0 +1,187 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<fim_prefix>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "<fim_middle>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"3": {
|
||||
"content": "<fim_suffix>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"4": {
|
||||
"content": "<fim_pad>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"5": {
|
||||
"content": "<filename>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"6": {
|
||||
"content": "<gh_stars>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"7": {
|
||||
"content": "<issue_start>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"8": {
|
||||
"content": "<issue_comment>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"9": {
|
||||
"content": "<issue_closed>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"10": {
|
||||
"content": "<jupyter_start>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"11": {
|
||||
"content": "<jupyter_text>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"12": {
|
||||
"content": "<jupyter_code>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"13": {
|
||||
"content": "<jupyter_output>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"14": {
|
||||
"content": "<empty_output>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"15": {
|
||||
"content": "<commit_before>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"16": {
|
||||
"content": "<commit_msg>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"17": {
|
||||
"content": "<commit_after>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"18": {
|
||||
"content": "<reponame>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"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": 9223372036854775807,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"tokenizer_class": "GPT2Tokenizer",
|
||||
"unk_token": "<|endoftext|>",
|
||||
"vocab_size": 49152
|
||||
}
|
||||
Reference in New Issue
Block a user