Text Generation
Transformers
PyTorch
English
qwen2
fuzzing
code-generation
grpo
rl
conversational
text-generation-inference
Instructions to use RLDriver/RLDriver-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RLDriver/RLDriver-32B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="RLDriver/RLDriver-32B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("RLDriver/RLDriver-32B") model = AutoModelForCausalLM.from_pretrained("RLDriver/RLDriver-32B") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use RLDriver/RLDriver-32B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RLDriver/RLDriver-32B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RLDriver/RLDriver-32B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/RLDriver/RLDriver-32B
- SGLang
How to use RLDriver/RLDriver-32B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "RLDriver/RLDriver-32B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RLDriver/RLDriver-32B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "RLDriver/RLDriver-32B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RLDriver/RLDriver-32B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use RLDriver/RLDriver-32B with Docker Model Runner:
docker model run hf.co/RLDriver/RLDriver-32B
Upload folder using huggingface_hub
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- .gitattributes +1 -0
- __pycache__/zero_to_fp32.cpython-312.pyc +0 -0
- added_tokens.json +24 -0
- chat_template.jinja +54 -0
- config.json +94 -0
- generation_config.json +13 -0
- global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +3 -0
- global_step100/bf16_zero_pp_rank_1_mp_rank_00_optim_states.pt +3 -0
- global_step100/bf16_zero_pp_rank_2_mp_rank_00_optim_states.pt +3 -0
- global_step100/bf16_zero_pp_rank_3_mp_rank_00_optim_states.pt +3 -0
- global_step100/bf16_zero_pp_rank_4_mp_rank_00_optim_states.pt +3 -0
- global_step100/bf16_zero_pp_rank_5_mp_rank_00_optim_states.pt +3 -0
- global_step100/bf16_zero_pp_rank_6_mp_rank_00_optim_states.pt +3 -0
- global_step100/bf16_zero_pp_rank_7_mp_rank_00_optim_states.pt +3 -0
- global_step100/zero_pp_rank_0_mp_rank_00_model_states.pt +3 -0
- global_step100/zero_pp_rank_1_mp_rank_00_model_states.pt +3 -0
- global_step100/zero_pp_rank_2_mp_rank_00_model_states.pt +3 -0
- global_step100/zero_pp_rank_3_mp_rank_00_model_states.pt +3 -0
- global_step100/zero_pp_rank_4_mp_rank_00_model_states.pt +3 -0
- global_step100/zero_pp_rank_5_mp_rank_00_model_states.pt +3 -0
- global_step100/zero_pp_rank_6_mp_rank_00_model_states.pt +3 -0
- global_step100/zero_pp_rank_7_mp_rank_00_model_states.pt +3 -0
- latest +1 -0
- merges.txt +0 -0
- pytorch_model-00001-of-00029.bin +3 -0
- pytorch_model-00002-of-00029.bin +3 -0
- pytorch_model-00003-of-00029.bin +3 -0
- pytorch_model-00004-of-00029.bin +3 -0
- pytorch_model-00005-of-00029.bin +3 -0
- pytorch_model-00006-of-00029.bin +3 -0
- pytorch_model-00007-of-00029.bin +3 -0
- pytorch_model-00008-of-00029.bin +3 -0
- pytorch_model-00009-of-00029.bin +3 -0
- pytorch_model-00010-of-00029.bin +3 -0
- pytorch_model-00011-of-00029.bin +3 -0
- pytorch_model-00012-of-00029.bin +3 -0
- pytorch_model-00013-of-00029.bin +3 -0
- pytorch_model-00014-of-00029.bin +3 -0
- pytorch_model-00015-of-00029.bin +3 -0
- pytorch_model-00016-of-00029.bin +3 -0
- pytorch_model-00017-of-00029.bin +3 -0
- pytorch_model-00018-of-00029.bin +3 -0
- pytorch_model-00019-of-00029.bin +3 -0
- pytorch_model-00020-of-00029.bin +3 -0
- pytorch_model-00021-of-00029.bin +3 -0
- pytorch_model-00022-of-00029.bin +3 -0
- pytorch_model-00023-of-00029.bin +3 -0
- pytorch_model-00024-of-00029.bin +3 -0
- pytorch_model-00025-of-00029.bin +3 -0
- pytorch_model-00026-of-00029.bin +3 -0
.gitattributes
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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__pycache__/zero_to_fp32.cpython-312.pyc
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added_tokens.json
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}
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0]['role'] == 'system' %}
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{{- messages[0]['content'] }}
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{%- else %}
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{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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{%- endif %}
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{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0]['role'] == 'system' %}
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{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role }}
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{%- if message.content %}
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{{- '\n' + message.content }}
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{%- endif %}
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{%- for tool_call in message.tool_calls %}
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{%- if tool_call.function is defined %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '\n<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{{- tool_call.arguments | tojson }}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- message.content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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config.json
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{
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"architectures": [
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"Qwen2ForCausalLM"
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],
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"attention_dropout": 0.0,
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"dtype": "bfloat16",
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"eos_token_id": 151645,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 27648,
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"layer_types": [
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention"
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],
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"max_position_embeddings": 32768,
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| 79 |
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"max_window_layers": 64,
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"model_type": "qwen2",
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| 81 |
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"num_attention_heads": 40,
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| 82 |
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"num_hidden_layers": 64,
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"num_key_value_heads": 8,
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| 84 |
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"pad_token_id": 151643,
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| 85 |
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"rms_norm_eps": 1e-06,
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| 86 |
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"rope_scaling": null,
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| 87 |
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.3",
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"use_cache": true,
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"use_sliding_window": false,
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"vocab_size": 152064
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}
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generation_config.json
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{
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"do_sample": true,
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| 3 |
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