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Model: JetBrains/Mellum-4b-sft-python Source: Original Platform
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README.md
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---
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license: apache-2.0
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datasets:
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- bigcode/the-stack
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- bigcode/the-stack-v2
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- bigcode/starcoderdata
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- bigcode/commitpack
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library_name: transformers
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tags:
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- code
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base_model:
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- JetBrains/Mellum-4b-base
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model-index:
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- name: Mellum-4b-sft-python
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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: tianyang/repobench_python_v1.1
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||||
name: RepoBench 1.1 (Python)
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metrics:
|
||||
- name: EM
|
||||
type: exact_match
|
||||
value: 0.2837
|
||||
verified: false
|
||||
- name: EM ≤ 8k
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||||
type: exact_match
|
||||
value: 0.2987
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||||
verified: false
|
||||
- task:
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type: text-generation
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dataset:
|
||||
type: tianyang/repobench_python_v1.1
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||||
name: RepoBench 1.1 (Python, 2k)
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||||
metrics:
|
||||
- name: EM
|
||||
type: exact_match
|
||||
value: 0.2924
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
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dataset:
|
||||
type: tianyang/repobench_python_v1.1
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||||
name: RepoBench 1.1 (Python, 4k)
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metrics:
|
||||
- name: EM
|
||||
type: exact_match
|
||||
value: 0.3060
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: tianyang/repobench_python_v1.1
|
||||
name: RepoBench 1.1 (Python, 8k)
|
||||
metrics:
|
||||
- name: EM
|
||||
type: exact_match
|
||||
value: 0.2977
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
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||||
dataset:
|
||||
type: tianyang/repobench_python_v1.1
|
||||
name: RepoBench 1.1 (Python, 12k)
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||||
metrics:
|
||||
- name: EM
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||||
type: exact_match
|
||||
value: 0.2680
|
||||
verified: false
|
||||
- task:
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||||
type: text-generation
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||||
dataset:
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||||
type: tianyang/repobench_python_v1.1
|
||||
name: RepoBench 1.1 (Python, 16k)
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||||
metrics:
|
||||
- name: EM
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||||
type: exact_match
|
||||
value: 0.2543
|
||||
verified: false
|
||||
- task:
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type: text-generation
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||||
dataset:
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||||
type: gonglinyuan/safim
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name: SAFIM
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||||
metrics:
|
||||
- name: pass@1
|
||||
type: pass@1
|
||||
value: 0.4212
|
||||
verified: false
|
||||
- task:
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||||
type: text-generation
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||||
dataset:
|
||||
type: gonglinyuan/safim
|
||||
name: SAFIM (Algorithmic)
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||||
metrics:
|
||||
- name: pass@1
|
||||
type: pass@1
|
||||
value: 0.3316
|
||||
verified: false
|
||||
- task:
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||||
type: text-generation
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||||
dataset:
|
||||
type: gonglinyuan/safim
|
||||
name: SAFIM (Control)
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||||
metrics:
|
||||
- name: pass@1
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||||
type: pass@1
|
||||
value: 0.3611
|
||||
verified: false
|
||||
- task:
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||||
type: text-generation
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||||
dataset:
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||||
type: gonglinyuan/safim
|
||||
name: SAFIM (API)
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||||
metrics:
|
||||
- name: pass@1
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||||
type: pass@1
|
||||
value: 0.5710
|
||||
verified: false
|
||||
- task:
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||||
type: text-generation
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||||
dataset:
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||||
type: loubnabnl/humaneval_infilling
|
||||
name: HumanEval Infilling (Single-Line)
|
||||
metrics:
|
||||
- name: pass@1
|
||||
type: pass@1
|
||||
value: 0.8045
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: loubnabnl/humaneval_infilling
|
||||
name: HumanEval Infilling (Multi-Line)
|
||||
metrics:
|
||||
- name: pass@1
|
||||
type: pass@1
|
||||
value: 0.4819
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: loubnabnl/humaneval_infilling
|
||||
name: HumanEval Infilling (Random Span)
|
||||
metrics:
|
||||
- name: pass@1
|
||||
type: pass@1
|
||||
value: 0.3768
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||||
verified: false
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---
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# Model Description
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Mellum-4b-sft-python is a fine-tuned version of JetBrains' first open-source large language model (LLM) optimized for code-related tasks.
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Pre-trained on over 4 trillion tokens with a context window of 8192 tokens across multiple programming languages, and then fine-tuned, Mellum-4b-sft-python is tailored specifically for code completion in Python.
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The model follows a LLaMA-style architecture with 4 billion parameters, making it efficient for both cloud inference (e.g., via vLLM) and local deployment (e.g., using llama.cpp or Ollama).
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Mellum was trained using Automatic Mixed Precision (AMP) with bf16 precision.
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The uploaded version on Hugging Face retains the bf16 format for public use.
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Designed for integration into professional developer tooling (e.g., intelligent code suggestions in IDEs), AI-powered coding assistants, and research on code understanding and generation, Mellum is also well-suited for educational applications and fine-tuning experiments.
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# Limitations
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- Biases: May reflect biases present in public codebases. For example it will likely produce code which is similar in style to the open-source repositories.
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- Security: Code suggestions should not be assumed to be secure or free of vulnerabilities.
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# Sample Usage
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Here is an example of how to run and sample from the model with additional files context and fill in the middle.
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## Fill in the middle with additional files as context generation
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```python
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import json
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from transformers import AutoTokenizer, AutoModelForCausalLM
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example = """<filename>utils.py
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def multiply(x, y):
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return x * y
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<filename>config.py
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DEBUG = True
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MAX_VALUE = 100
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<filename>example.py
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<fim_suffix>
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# Test the function
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result = calculate_sum(5, 10)
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print(result)<fim_prefix>def calculate_sum(a, b):
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<fim_middle>"""
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tokenizer = AutoTokenizer.from_pretrained('JetBrains/Mellum-4b-sft-python')
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model = AutoModelForCausalLM.from_pretrained('JetBrains/MMellum-4b-sft-python')
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encoded_input = tokenizer(example, return_tensors='pt', return_token_type_ids=False)
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out = model.generate(
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**encoded_input,
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max_new_tokens=100,
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)
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```
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# Citation
|
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If you use this model, please cite:
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||||
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||||
```bibtex
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||||
@misc{Mellum-4b-base,
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title = {Mellum-4b-base},
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||||
author = {Pavlichenko, Nikita and Nazarov, Iurii and Dolgov, Ivan and Garanina, Ekaterina and Lasocki, Karol and Reshetnikova, Julia and Boitsov, Sergei and Bondyrev, Ivan and Karaeva, Dariia and Sheptyakov, Maksim and Ustalov, Dmitry and Mukhin, Artem and Proshev, Semyon and Abramov, Nikita and Kolomyttseva, Olga and Lysaniuk, Kseniia and Zavidnyi, Ilia and Semenkin, Anton and Tankov, Vladislav and Sazanovich, Uladzislau},
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year = {2025},
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}
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```
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# Contact
|
||||
For questions, collaborations and requests reach us out via mellum@jetbrains.com
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config.json
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{
|
||||
"architectures": [
|
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"LlamaForCausalLM"
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||||
],
|
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"attention_bias": false,
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"attention_dropout": 0.0,
|
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"bos_token_id": 0,
|
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"eos_token_id": 0,
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"head_dim": 128,
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"hidden_act": "silu",
|
||||
"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 8256,
|
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"max_position_embeddings": 8192,
|
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"max_sequence_length": 8192,
|
||||
"mlp_bias": false,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 24,
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"num_hidden_layers": 30,
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"num_key_value_heads": 24,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
|
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"rope_scaling": null,
|
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"rope_theta": 500000.0,
|
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"tie_word_embeddings": false,
|
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"torch_dtype": "bfloat16",
|
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"transformers_version": "4.51.3",
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"use_cache": true,
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"vocab_size": 98304
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}
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1
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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}
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
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|
||||
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|
||||
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|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
58
special_tokens_map.json
Normal file
58
special_tokens_map.json
Normal file
@@ -0,0 +1,58 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<gh_stars>",
|
||||
"</system>",
|
||||
"<issue_start>",
|
||||
"</think>",
|
||||
"<commit_after>",
|
||||
"<assistant>",
|
||||
"<jupyter_text>",
|
||||
"<fim_middle>",
|
||||
"</assistant>",
|
||||
"<jupyter_code>",
|
||||
"<user>",
|
||||
"<filename>",
|
||||
"<think>",
|
||||
"<fim_suffix>",
|
||||
"<fim_prefix>",
|
||||
"<commit_msg>",
|
||||
"<fim_pad>",
|
||||
"<system>",
|
||||
"<issue_comment>",
|
||||
"<reponame>",
|
||||
"<jupyter_start>",
|
||||
"<issue_closed>",
|
||||
"<commit_before>",
|
||||
"<empty_output>",
|
||||
"<jupyter_output>",
|
||||
"</user>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"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 sha256:9fa1151bc9cc1c9f133845e8100c91fbd7746f9f4abe69888c2ddc9f771978b0
|
||||
size 7030308
|
||||
259
tokenizer_config.json
Normal file
259
tokenizer_config.json
Normal file
@@ -0,0 +1,259 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"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
|
||||
},
|
||||
"19": {
|
||||
"content": "<system>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"20": {
|
||||
"content": "</system>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"21": {
|
||||
"content": "<user>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"22": {
|
||||
"content": "</user>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"23": {
|
||||
"content": "<assistant>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"24": {
|
||||
"content": "</assistant>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"25": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"26": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<gh_stars>",
|
||||
"</system>",
|
||||
"<issue_start>",
|
||||
"</think>",
|
||||
"<commit_after>",
|
||||
"<assistant>",
|
||||
"<jupyter_text>",
|
||||
"<fim_middle>",
|
||||
"</assistant>",
|
||||
"<jupyter_code>",
|
||||
"<user>",
|
||||
"<filename>",
|
||||
"<think>",
|
||||
"<fim_suffix>",
|
||||
"<fim_prefix>",
|
||||
"<commit_msg>",
|
||||
"<fim_pad>",
|
||||
"<system>",
|
||||
"<issue_comment>",
|
||||
"<reponame>",
|
||||
"<jupyter_start>",
|
||||
"<issue_closed>",
|
||||
"<commit_before>",
|
||||
"<empty_output>",
|
||||
"<jupyter_output>",
|
||||
"</user>"
|
||||
],
|
||||
"bos_token": "<|endoftext|>",
|
||||
"clean_up_tokenization_spaces": true,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"tokenizer_class": "GPT2Tokenizer",
|
||||
"unk_token": "<|endoftext|>"
|
||||
}
|
||||
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