Text Generation
PEFT
Safetensors
clinical-trial
reinforcement-learning
REINFORCE
lora
qwen3
openenv
hackathon
theme-2
conversational
Instructions to use pratimassaravanan/clinical-qwen3-4b-sft-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use pratimassaravanan/clinical-qwen3-4b-sft-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-4B-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "pratimassaravanan/clinical-qwen3-4b-sft-lora") - Notebooks
- Google Colab
- Kaggle
Upload eval_results.json with huggingface_hub
Browse files- eval_results.json +35 -0
eval_results.json
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{
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"easy_bench": {
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"task": "easy_bench",
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"steps": 50,
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"total_reward": 6.4762,
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"enrolled": 0,
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"target": 100,
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"json_parse_rate": 1.0,
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"action_dist": {
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"adjust_strategy": 50
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"medium_bench": {
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"task": "medium_bench",
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"steps": 50,
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"total_reward": 1.5398,
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"enrolled": 0,
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"target": 100,
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"json_parse_rate": 1.0,
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"action_dist": {
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"adjust_strategy": 50
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"hard_bench": {
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"task": "hard_bench",
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"steps": 50,
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"total_reward": 3.0742,
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"enrolled": 0,
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"target": 100,
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"json_parse_rate": 1.0,
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"action_dist": {
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"adjust_strategy": 50
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}
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