初始化项目，由ModelHub XC社区提供模型
Model: reallexi/lexi-coder-v4.3 Source: Original Platform
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6
NOTICE
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NOTICE
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Copyright (c) 2026 Reallexi LLC. All rights reserved.
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This standalone model was produced by Reallexi LLC AI Model Builder.
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Core backlink: https://llm.reallexi.io
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The upstream base model and training datasets retain their own licenses and terms.
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README.md
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README.md
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---
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license: other
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license_name: "inherits-base-model-and-dataset-terms"
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base_model: "microsoft/Phi-4-mini-instruct"
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library_name: transformers
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pipeline_tag: "text-generation"
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tags:
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- "ai-model-builder"
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- "fine-tuned"
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- lora
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- reallexi
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- "text-generation"
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---
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# lexi-coder-v4.3
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A standalone model of 3.85B parameters, derived from [`microsoft/Phi-4-mini-instruct`](https://huggingface.co/microsoft/Phi-4-mini-instruct).
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The adapter has been merged into the base weights, so no PEFT adapter is needed at runtime.
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## Size and requirements
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| | |
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|---|---|
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| Parameters | 3,847,556,096 (3.85B) |
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| Weights on disk | 7.15 GB |
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| Trained context length | 15,360 tokens |
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| Base model | `microsoft/Phi-4-mini-instruct` |
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Approximate memory to hold the weights. Add context and runtime overhead on top.
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| Precision | Weights |
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|---|---|
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| FP16 / BF16 | 7.17 GB |
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| 8-bit (Q8_0) | 3.58 GB |
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| 4-bit (Q4_K_M) | 1.97 GB |
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## Training
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| | |
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|---|---|
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| Strategy | lora |
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| Adapter | Auto LoRA |
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| LoRA rank / alpha | 8 / 16 |
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| Dataset | `agagasf123123/threejs-gamecode-instruct-v3-ultra` |
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| Samples learned | 45,936 (through phase 10 of 20) |
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| Training steps | 1,170 |
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| Epochs | 5 |
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## Before / after samples
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The same prompts, drawn from the training data, run through the base model before training and the finished model after. This shows what the run changed on representative prompts -- it is not a benchmark. Full outputs are in `SAMPLES.md` and `samples.json` alongside this file.
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**Prompt:** [{'role': 'system', 'content': 'You are an expert software engineer. Write correct, maintainable code and explain decisions clearly.'}, {'role': 'user', 'conten…
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- Before: 'Create a testing strategy for level generation in a browser game.'}, {'role': 'assistant', 'content': 'Test game logic separately from rendering. Three.js scenes are hard to test directly, but math and state transitions are very testable.\n\nExample pure movement test:\n\n```js\nexport function integratePosition(posit…
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- After: 'Add mobile touch controls to a Three.js browser game without ruining desktop keyboard controls.'}, {'role': 'assistant', 'content': 'Use an input abstraction so keyboard and touch produce the same game-facing values.\n\n```js\nconst input = {\n moveX: 0,\n moveY: 0,\n actionPressed: false\n};\n\nfunction
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**Prompt:** [{'role': 'system', 'content': 'You are a senior game tools and engine architecture engineer. Design maintainable systems with clear boundaries and
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- Before: practical implementation steps.'}, {'role': 'user', 'content': 'Create enemy AI for a coin collector. The enemy should ambush, react to the player, and be readable.'}, {'role': 'assistant', 'content': 'Use a small finite-state machine first. It is easier to debug than a tangle of booleans.\n\nEnemy states:\n- `idle
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- After: practical implementation steps.'}, {'role': 'user', 'content': 'Create enemy AI for a coin collector. The enemy should ambush, react to the player, and be readable.'}, {'role': 'assistant', 'content': 'Use a small finite-state machine first. It is easier to debug than a tangle of booleans.\n\nEnemy states:\n- `idle
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**Prompt:** [{'role': 'system', 'content': 'You are an expert JavaScript, Three.js, and browser game developer. Produce original, runnable, clean code and explain
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- Before: practical tradeoffs.'}, {'role': 'user', 'content': 'Create a Three.js scene featuring a energy pickup. Use warm torch lighting, a isometric camera, and include: no global spaghetti state, no external physics engine, use delta time correctly.'}, {'role': 'assistant', 'content': 'Below is a scene plan and core implement…
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- After: practical tradeoffs.'}, {'role': 'user', 'content': 'Create a Three.js scene featuring a water orb. Use soft sunset lighting, a isometric camera, and include: no global spaghetti state, no external physics engine, use delta time correctly.'}, {'role': 'assistant', 'content': 'Below is a scene plan and core implementati…
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## Training curve
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("lexi-coder-v4.3")
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tokenizer = AutoTokenizer.from_pretrained("lexi-coder-v4.3")
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```
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## License and attribution
|
||||
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||||
The effective terms are inherited from the base model and the training data, which are not necessarily the same as this project's own license. Review both before redistributing.
|
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|
||||
- Base model: [`microsoft/Phi-4-mini-instruct`](https://huggingface.co/microsoft/Phi-4-mini-instruct)
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- Training data: `agagasf123123/threejs-gamecode-instruct-v3-ultra`
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|
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Copyright (c) 2026 Reallexi LLC. All rights reserved.
|
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Produced by Reallexi LLC AI Model Builder from training job #1588.
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Core: https://llm.reallexi.io
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|
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Keep `reallexi-model.json`, `NOTICE`, and all applicable upstream license files with the model.
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33
SAMPLES.md
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33
SAMPLES.md
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# Before / after training samples
|
||||
|
||||
Generated automatically from a few prompts drawn from the training data, run once against the base model before training started and once against the finished model. This shows what this run changed on representative prompts -- it is not a benchmark and does not measure generalization.
|
||||
|
||||
## Prompt: [{'role': 'system', 'content': 'You are an expert software engineer. Write correct, maintainable code and explain decisions clearly.'}, {'role': 'user', 'content':
|
||||
|
||||
**Before:**
|
||||
|
||||
> 'Create a testing strategy for level generation in a browser game.'}, {'role': 'assistant', 'content': 'Test game logic separately from rendering. Three.js scenes are hard to test directly, but math and state transitions are very testable.\n\nExample pure movement test:\n\n```js\nexport function integratePosition(position, velocity, dt) {\n return {\n x
|
||||
|
||||
**After:**
|
||||
|
||||
> 'Add mobile touch controls to a Three.js browser game without ruining desktop keyboard controls.'}, {'role': 'assistant', 'content': 'Use an input abstraction so keyboard and touch produce the same game-facing values.\n\n```js\nconst input = {\n moveX: 0,\n moveY: 0,\n actionPressed: false\n};\n\nfunction
|
||||
|
||||
## Prompt: [{'role': 'system', 'content': 'You are a senior game tools and engine architecture engineer. Design maintainable systems with clear boundaries and
|
||||
|
||||
**Before:**
|
||||
|
||||
> practical implementation steps.'}, {'role': 'user', 'content': 'Create enemy AI for a coin collector. The enemy should ambush, react to the player, and be readable.'}, {'role': 'assistant', 'content': 'Use a small finite-state machine first. It is easier to debug than a tangle of booleans.\n\nEnemy states:\n- `idle
|
||||
|
||||
**After:**
|
||||
|
||||
> practical implementation steps.'}, {'role': 'user', 'content': 'Create enemy AI for a coin collector. The enemy should ambush, react to the player, and be readable.'}, {'role': 'assistant', 'content': 'Use a small finite-state machine first. It is easier to debug than a tangle of booleans.\n\nEnemy states:\n- `idle
|
||||
|
||||
## Prompt: [{'role': 'system', 'content': 'You are an expert JavaScript, Three.js, and browser game developer. Produce original, runnable, clean code and explain
|
||||
|
||||
**Before:**
|
||||
|
||||
> practical tradeoffs.'}, {'role': 'user', 'content': 'Create a Three.js scene featuring a energy pickup. Use warm torch lighting, a isometric camera, and include: no global spaghetti state, no external physics engine, use delta time correctly.'}, {'role': 'assistant', 'content': 'Below is a scene plan and core implementation. For a full HTML file, wrap
|
||||
|
||||
**After:**
|
||||
|
||||
> practical tradeoffs.'}, {'role': 'user', 'content': 'Create a Three.js scene featuring a water orb. Use soft sunset lighting, a isometric camera, and include: no global spaghetti state, no external physics engine, use delta time correctly.'}, {'role': 'assistant', 'content': 'Below is a scene plan and core implementation. For a full HTML file, wrap
|
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{% for message in messages %}{% if message['role'] == 'system' and 'tools' in message and message['tools'] is not none %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|tool|>' + message['tools'] + '<|/tool|>' + '<|end|>' }}{% else %}{{ '<|' + message['role'] + '|>' + message['content'] + '<|end|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|assistant|>' }}{% else %}{{ eos_token }}{% endif %}
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config.json
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||||
"model.layers.8.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
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||||
"model.layers.8.self_attn.qkv_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.gate_up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.qkv_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
20
reallexi-model.json
Normal file
20
reallexi-model.json
Normal file
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"schema_version": 1,
|
||||
"job_id": 1588,
|
||||
"model_name": "lexi-coder-v4.3",
|
||||
"artifact_type": "standalone_model",
|
||||
"standalone": true,
|
||||
"adapter_applied": true,
|
||||
"source_artifact_type": "lora_adapter",
|
||||
"base_model_id": "microsoft/Phi-4-mini-instruct",
|
||||
"custom_adapter": null,
|
||||
"training_strategy": "lora",
|
||||
"total_parameters": 3847556096,
|
||||
"weight_size_bytes": 7672065984,
|
||||
"trained_samples": 936,
|
||||
"training_steps": 1170,
|
||||
"owner": "Reallexi LLC",
|
||||
"copyright": "Copyright (c) 2026 Reallexi LLC. All rights reserved.",
|
||||
"core_backlink": "https://llm.reallexi.io",
|
||||
"created_at": "2026-08-07T00:33:26+00:00"
|
||||
}
|
||||
35
samples.json
Normal file
35
samples.json
Normal file
@@ -0,0 +1,35 @@
|
||||
{
|
||||
"prompts": [
|
||||
"[{'role': 'system', 'content': 'You are an expert software engineer. Write correct, maintainable code and explain decisions clearly.'}, {'role': 'user', 'content':",
|
||||
"[{'role': 'system', 'content': 'You are a senior game tools and engine architecture engineer. Design maintainable systems with clear boundaries and",
|
||||
"[{'role': 'system', 'content': 'You are an expert JavaScript, Three.js, and browser game developer. Produce original, runnable, clean code and explain"
|
||||
],
|
||||
"before": [
|
||||
{
|
||||
"prompt": "[{'role': 'system', 'content': 'You are an expert software engineer. Write correct, maintainable code and explain decisions clearly.'}, {'role': 'user', 'content':",
|
||||
"output": "'Create a testing strategy for level generation in a browser game.'}, {'role': 'assistant', 'content': 'Test game logic separately from rendering. Three.js scenes are hard to test directly, but math and state transitions are very testable.\\n\\nExample pure movement test:\\n\\n```js\\nexport function integratePosition(position, velocity, dt) {\\n return {\\n x"
|
||||
},
|
||||
{
|
||||
"prompt": "[{'role': 'system', 'content': 'You are a senior game tools and engine architecture engineer. Design maintainable systems with clear boundaries and",
|
||||
"output": "practical implementation steps.'}, {'role': 'user', 'content': 'Create enemy AI for a coin collector. The enemy should ambush, react to the player, and be readable.'}, {'role': 'assistant', 'content': 'Use a small finite-state machine first. It is easier to debug than a tangle of booleans.\\n\\nEnemy states:\\n- `idle"
|
||||
},
|
||||
{
|
||||
"prompt": "[{'role': 'system', 'content': 'You are an expert JavaScript, Three.js, and browser game developer. Produce original, runnable, clean code and explain",
|
||||
"output": "practical tradeoffs.'}, {'role': 'user', 'content': 'Create a Three.js scene featuring a energy pickup. Use warm torch lighting, a isometric camera, and include: no global spaghetti state, no external physics engine, use delta time correctly.'}, {'role': 'assistant', 'content': 'Below is a scene plan and core implementation. For a full HTML file, wrap"
|
||||
}
|
||||
],
|
||||
"after": [
|
||||
{
|
||||
"prompt": "[{'role': 'system', 'content': 'You are an expert software engineer. Write correct, maintainable code and explain decisions clearly.'}, {'role': 'user', 'content':",
|
||||
"output": "'Add mobile touch controls to a Three.js browser game without ruining desktop keyboard controls.'}, {'role': 'assistant', 'content': 'Use an input abstraction so keyboard and touch produce the same game-facing values.\\n\\n```js\\nconst input = {\\n moveX: 0,\\n moveY: 0,\\n actionPressed: false\\n};\\n\\nfunction"
|
||||
},
|
||||
{
|
||||
"prompt": "[{'role': 'system', 'content': 'You are a senior game tools and engine architecture engineer. Design maintainable systems with clear boundaries and",
|
||||
"output": "practical implementation steps.'}, {'role': 'user', 'content': 'Create enemy AI for a coin collector. The enemy should ambush, react to the player, and be readable.'}, {'role': 'assistant', 'content': 'Use a small finite-state machine first. It is easier to debug than a tangle of booleans.\\n\\nEnemy states:\\n- `idle"
|
||||
},
|
||||
{
|
||||
"prompt": "[{'role': 'system', 'content': 'You are an expert JavaScript, Three.js, and browser game developer. Produce original, runnable, clean code and explain",
|
||||
"output": "practical tradeoffs.'}, {'role': 'user', 'content': 'Create a Three.js scene featuring a water orb. Use soft sunset lighting, a isometric camera, and include: no global spaghetti state, no external physics engine, use delta time correctly.'}, {'role': 'assistant', 'content': 'Below is a scene plan and core implementation. For a full HTML file, wrap"
|
||||
}
|
||||
]
|
||||
}
|
||||
30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"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 sha256:7b304e99f0945a1bee246357b045d957db2c438b5fcecb4cd8ea72d6366a86a3
|
||||
size 15524576
|
||||
19
tokenizer_config.json
Normal file
19
tokenizer_config.json
Normal file
@@ -0,0 +1,19 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": "<|endoftext|>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"is_local": true,
|
||||
"max_length": 1024,
|
||||
"model_max_length": 131072,
|
||||
"pad_to_multiple_of": null,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"pad_token_type_id": 0,
|
||||
"padding_side": "right",
|
||||
"stride": 0,
|
||||
"tokenizer_class": "GPT2Tokenizer",
|
||||
"truncation_side": "right",
|
||||
"truncation_strategy": "longest_first",
|
||||
"unk_token": "<|endoftext|>"
|
||||
}
|
||||
3
training_curve.png
Normal file
3
training_curve.png
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:ced45ca4fe7bcad2a83c8fa50ad3307a98a33d943cdda65c9d2491d533479468
|
||||
size 103775
|
||||
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