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and-de/t5-educhat-finetuned | and-de | "2024-09-30T22:59:52Z" | 0 | 0 | transformers | [
"transformers",
"tensorboard",
"safetensors",
"t5",
"text2text-generation",
"arxiv:1910.09700",
"autotrain_compatible",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] | text2text-generation | "2024-09-26T04:28:14Z" | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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SALUTEASD/Qwen-Qwen1.5-1.8B-1727324934 | SALUTEASD | "2024-09-26T04:29:01Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:28:54Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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jerseyjerry/google-gemma-2b-it-1727324947 | jerseyjerry | "2024-09-26T04:29:15Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b-it",
"base_model:adapter:google/gemma-2b-it",
"region:us"
] | null | "2024-09-26T04:29:07Z" | ---
base_model: google/gemma-2b-it
library_name: peft
---
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dogssss/Qwen-Qwen1.5-1.8B-1727324995 | dogssss | "2024-09-26T04:29:59Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:29:56Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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latiao1999/Qwen-Qwen1.5-1.8B-1727324997 | latiao1999 | "2024-09-26T04:30:03Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:29:57Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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kavish218/finetuned_llama_3_2_1B_lora_model | kavish218 | "2024-09-26T04:30:27Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T04:30:20Z" | ---
base_model: unsloth/llama-3.2-1b-instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** kavish218
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3.2-1b-instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
smeby/Qwen-Qwen1.5-0.5B-1727325045 | smeby | "2024-09-26T04:30:48Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:30:46Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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AvniMittal13/shwartz2_normal | AvniMittal13 | "2024-09-26T04:30:51Z" | 0 | 0 | transformers | [
"transformers",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T04:30:49Z" | ---
library_name: transformers
tags: []
---
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SALUTEASD/google-gemma-2b-1727325097 | SALUTEASD | "2024-09-26T04:31:49Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T04:31:37Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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saqqdy/Qwen-Qwen1.5-1.8B-1727325241 | saqqdy | "2024-09-26T04:34:05Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:34:01Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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IAMTHEMUSIC/Travis-Scott-Official | IAMTHEMUSIC | "2024-09-26T04:34:52Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T04:34:07Z" | Entry not found |
smeby/Qwen-Qwen1.5-1.8B-1727325267 | smeby | "2024-09-26T04:34:29Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:34:27Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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dogssss/Qwen-Qwen1.5-0.5B-1727325311 | dogssss | "2024-09-26T04:35:15Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:35:12Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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### Framework versions
- PEFT 0.12.0 |
Gloaustinlm123/Miriotogata | Gloaustinlm123 | "2024-09-26T04:36:27Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T04:35:28Z" | Entry not found |
pepper13/fluxnfw | pepper13 | "2024-09-26T04:50:46Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T04:36:33Z" | Entry not found |
1rsh/Llama-3.2-3B-fr | 1rsh | "2024-09-26T04:37:29Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T04:37:15Z" | ---
base_model: unsloth/llama-3.2-3b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** 1rsh
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3.2-3b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
SALUTEASD/Qwen-Qwen1.5-1.8B-1727325501 | SALUTEASD | "2024-09-26T04:38:26Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:38:21Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
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Krabat/Qwen-Qwen1.5-0.5B-1727325596 | Krabat | "2024-09-26T04:39:59Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:39:56Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- PEFT 0.12.0 |
siswabaru001/finetuned2-bge-m3_info11 | siswabaru001 | "2024-09-26T04:40:13Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T04:40:13Z" | Entry not found |
qurratulain033/cnn_news_summary_model_trained_on_reduced_data | qurratulain033 | "2024-09-26T04:40:18Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T04:40:18Z" | Entry not found |
saqqdy/Qwen-Qwen1.5-0.5B-1727325627 | saqqdy | "2024-09-26T04:40:32Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:40:28Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
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dogssss/Qwen-Qwen1.5-1.8B-1727325649 | dogssss | "2024-09-26T04:40:53Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:40:50Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
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SALUTEASD/google-gemma-2b-1727325666 | SALUTEASD | "2024-09-26T04:41:18Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T04:41:07Z" | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
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[More Information Needed]
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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xnoeleonx/dqn-SpaceInvadersNoFrameskip-v4 | xnoeleonx | "2024-09-29T15:49:51Z" | 0 | 0 | stable-baselines3 | [
"stable-baselines3",
"SpaceInvadersNoFrameskip-v4",
"deep-reinforcement-learning",
"reinforcement-learning",
"model-index",
"region:us"
] | reinforcement-learning | "2024-09-26T04:41:15Z" | ---
library_name: stable-baselines3
tags:
- SpaceInvadersNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SpaceInvadersNoFrameskip-v4
type: SpaceInvadersNoFrameskip-v4
metrics:
- type: mean_reward
value: 402.00 +/- 103.57
name: mean_reward
verified: false
---
# **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.
## Usage (with SB3 RL Zoo)
RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
Install the RL Zoo (with SB3 and SB3-Contrib):
```bash
pip install rl_zoo3
```
```
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga xnoeleonx -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
```
If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
```
python -m rl_zoo3.load_from_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -orga xnoeleonx -f logs/
python -m rl_zoo3.enjoy --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
```
## Training (with the RL Zoo)
```
python -m rl_zoo3.train --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo dqn --env SpaceInvadersNoFrameskip-v4 -f logs/ -orga xnoeleonx
```
## Hyperparameters
```python
OrderedDict([('batch_size', 32),
('buffer_size', 100000),
('env_wrapper',
['stable_baselines3.common.atari_wrappers.AtariWrapper']),
('exploration_final_eps', 0.01),
('exploration_fraction', 0.1),
('frame_stack', 4),
('gradient_steps', 1),
('learning_rate', 0.0001),
('learning_starts', 100000),
('n_timesteps', 500000.0),
('optimize_memory_usage', False),
('policy', 'CnnPolicy'),
('target_update_interval', 1000),
('train_freq', 4),
('normalize', False)])
```
# Environment Arguments
```python
{'render_mode': 'rgb_array'}
```
|
smeby/Qwen-Qwen1.5-0.5B-1727325689 | smeby | "2024-09-26T04:41:31Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:41:29Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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SALUTEASD/Qwen-Qwen1.5-0.5B-1727325878 | SALUTEASD | "2024-09-26T04:44:43Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:44:38Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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smeby/Qwen-Qwen1.5-1.8B-1727325881 | smeby | "2024-09-26T04:44:43Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:44:41Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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dogssss/Qwen-Qwen1.5-0.5B-1727325941 | dogssss | "2024-09-26T04:45:45Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:45:42Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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saqqdy/Qwen-Qwen1.5-1.8B-1727326001 | saqqdy | "2024-09-26T04:46:45Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:46:41Z" | ---
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library_name: peft
---
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Soheil77/ZexMoel | Soheil77 | "2024-09-26T05:06:14Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-09-26T04:47:15Z" | ---
license: openrail
---
|
smeby/google-gemma-2b-1727326046 | smeby | "2024-09-26T04:47:34Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T04:47:26Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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jerseyjerry/Qwen-Qwen2-0.5B-Instruct-1727326112 | jerseyjerry | "2024-09-26T04:48:38Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-0.5B-Instruct",
"base_model:adapter:Qwen/Qwen2-0.5B-Instruct",
"region:us"
] | null | "2024-09-26T04:48:33Z" | ---
base_model: Qwen/Qwen2-0.5B-Instruct
library_name: peft
---
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latiao1999/google-gemma-2b-1727326157 | latiao1999 | "2024-09-26T04:49:27Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T04:49:17Z" | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
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dogssss/Qwen-Qwen1.5-1.8B-1727326251 | dogssss | "2024-09-26T04:50:56Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:50:52Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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smeby/Qwen-Qwen1.5-0.5B-1727326266 | smeby | "2024-09-26T04:51:08Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:51:06Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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SALUTEASD/google-gemma-2b-1727326280 | SALUTEASD | "2024-09-26T04:51:36Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T04:51:20Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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Krabat/Qwen-Qwen1.5-1.8B-1727326378 | Krabat | "2024-09-26T04:53:00Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:52:58Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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saqqdy/Qwen-Qwen1.5-0.5B-1727326382 | saqqdy | "2024-09-26T04:53:07Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:53:03Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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jerseyjerry/Qwen-Qwen2-0.5B-1727326411 | jerseyjerry | "2024-09-26T04:53:36Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-0.5B",
"base_model:adapter:Qwen/Qwen2-0.5B",
"region:us"
] | null | "2024-09-26T04:53:31Z" | ---
base_model: Qwen/Qwen2-0.5B
library_name: peft
---
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smeby/Qwen-Qwen1.5-1.8B-1727326483 | smeby | "2024-09-26T04:54:45Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:54:43Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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dogssss/Qwen-Qwen1.5-0.5B-1727326533 | dogssss | "2024-09-26T04:55:37Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T04:55:34Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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Krabat/google-gemma-2b-1727326541 | Krabat | "2024-09-26T04:55:45Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T04:55:41Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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nasassass/real_nas26758032 | nasassass | "2024-09-26T04:55:54Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T04:55:53Z" | Entry not found |
smeby/google-gemma-2b-1727326660 | smeby | "2024-09-26T04:57:42Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T04:57:40Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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SALUTEASD/Qwen-Qwen1.5-1.8B-1727326686 | SALUTEASD | "2024-09-26T04:58:11Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:58:07Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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Krabat/google-gemma-7b-1727326750 | Krabat | "2024-09-26T04:59:12Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-7b",
"base_model:adapter:google/gemma-7b",
"region:us"
] | null | "2024-09-26T04:59:10Z" | ---
base_model: google/gemma-7b
library_name: peft
---
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saqqdy/Qwen-Qwen1.5-1.8B-1727326755 | saqqdy | "2024-09-26T04:59:19Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T04:59:15Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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AvniMittal13/shwartz3 | AvniMittal13 | "2024-09-26T05:02:23Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:microsoft/phi-2",
"base_model:adapter:microsoft/phi-2",
"region:us"
] | null | "2024-09-26T04:59:26Z" | ---
base_model: microsoft/phi-2
library_name: peft
---
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jerseyjerry/Qwen-Qwen2-1.5B-1727326796 | jerseyjerry | "2024-09-26T05:00:01Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-1.5B",
"base_model:adapter:Qwen/Qwen2-1.5B",
"region:us"
] | null | "2024-09-26T04:59:56Z" | ---
base_model: Qwen/Qwen2-1.5B
library_name: peft
---
# Model Card for Model ID
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luaqi/nas39233799 | luaqi | "2024-09-26T05:00:35Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T05:00:34Z" | Entry not found |
dogssss/Qwen-Qwen1.5-1.8B-1727326843 | dogssss | "2024-09-26T05:00:46Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:00:44Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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SALUTEASD/google-gemma-2b-1727326847 | SALUTEASD | "2024-09-26T05:00:56Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T05:00:47Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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Armun86/Q | Armun86 | "2024-09-26T05:01:07Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T05:01:07Z" | Entry not found |
haryoaw/scenario-kd-scr-ner-half-xlmr_data-univner_full55 | haryoaw | "2024-10-01T15:14:17Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"generated_from_trainer",
"base_model:haryoaw/scenario-TCR-NER_data-univner_full",
"base_model:finetune:haryoaw/scenario-TCR-NER_data-univner_full",
"license:mit",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T05:01:18Z" | ---
base_model: haryoaw/scenario-TCR-NER_data-univner_full
library_name: transformers
license: mit
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: scenario-kd-scr-ner-half-xlmr_data-univner_full55
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# scenario-kd-scr-ner-half-xlmr_data-univner_full55
This model is a fine-tuned version of [haryoaw/scenario-TCR-NER_data-univner_full](https://huggingface.co/haryoaw/scenario-TCR-NER_data-univner_full) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 120.6184
- Precision: 0.4401
- Recall: 0.4037
- F1: 0.4211
- Accuracy: 0.9497
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 55
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 257.0107 | 0.2911 | 500 | 189.5383 | 0.0 | 0.0 | 0.0 | 0.9241 |
| 178.7712 | 0.5822 | 1000 | 172.3710 | 0.3271 | 0.0127 | 0.0244 | 0.9246 |
| 167.3858 | 0.8732 | 1500 | 164.0120 | 0.1535 | 0.0169 | 0.0304 | 0.9249 |
| 160.7425 | 1.1643 | 2000 | 158.6453 | 0.2922 | 0.0205 | 0.0383 | 0.9251 |
| 155.1095 | 1.4554 | 2500 | 154.0389 | 0.1211 | 0.0264 | 0.0434 | 0.9255 |
| 151.9538 | 1.7465 | 3000 | 151.6052 | 0.2305 | 0.0906 | 0.1301 | 0.9277 |
| 147.3667 | 2.0375 | 3500 | 148.2291 | 0.2940 | 0.0456 | 0.0789 | 0.9263 |
| 144.7168 | 2.3286 | 4000 | 144.3864 | 0.3148 | 0.0848 | 0.1337 | 0.9279 |
| 141.0402 | 2.6197 | 4500 | 141.7098 | 0.2923 | 0.1097 | 0.1595 | 0.9292 |
| 138.8105 | 2.9108 | 5000 | 139.1967 | 0.2783 | 0.1482 | 0.1934 | 0.9317 |
| 135.7546 | 3.2019 | 5500 | 137.3528 | 0.2659 | 0.1244 | 0.1695 | 0.9315 |
| 133.9791 | 3.4929 | 6000 | 135.2162 | 0.2938 | 0.1721 | 0.2171 | 0.9334 |
| 132.2804 | 3.7840 | 6500 | 133.5810 | 0.2993 | 0.1783 | 0.2235 | 0.9349 |
| 129.821 | 4.0751 | 7000 | 132.0036 | 0.2955 | 0.2072 | 0.2436 | 0.9365 |
| 128.3417 | 4.3662 | 7500 | 130.7451 | 0.3180 | 0.2342 | 0.2697 | 0.9379 |
| 126.945 | 4.6573 | 8000 | 129.4695 | 0.3192 | 0.2461 | 0.2780 | 0.9392 |
| 125.4315 | 4.9483 | 8500 | 128.3516 | 0.3394 | 0.2538 | 0.2904 | 0.9403 |
| 124.2135 | 5.2394 | 9000 | 127.4555 | 0.3510 | 0.2938 | 0.3198 | 0.9416 |
| 122.2169 | 5.5305 | 9500 | 127.0589 | 0.3286 | 0.3086 | 0.3183 | 0.9405 |
| 121.9071 | 5.8216 | 10000 | 125.9840 | 0.3894 | 0.3008 | 0.3394 | 0.9437 |
| 121.5513 | 6.1126 | 10500 | 124.8811 | 0.3905 | 0.3295 | 0.3574 | 0.9448 |
| 120.0176 | 6.4037 | 11000 | 124.4447 | 0.3919 | 0.3320 | 0.3594 | 0.9446 |
| 119.3149 | 6.6948 | 11500 | 123.5647 | 0.3979 | 0.3577 | 0.3767 | 0.9467 |
| 118.4263 | 6.9859 | 12000 | 123.1085 | 0.4221 | 0.3614 | 0.3894 | 0.9473 |
| 117.173 | 7.2770 | 12500 | 122.7588 | 0.4139 | 0.3668 | 0.3889 | 0.9477 |
| 117.0076 | 7.5680 | 13000 | 122.3339 | 0.4198 | 0.3702 | 0.3934 | 0.9476 |
| 116.7387 | 7.8591 | 13500 | 121.8244 | 0.4275 | 0.3885 | 0.4071 | 0.9483 |
| 116.1363 | 8.1502 | 14000 | 121.4477 | 0.4337 | 0.3958 | 0.4139 | 0.9492 |
| 115.5528 | 8.4413 | 14500 | 121.2595 | 0.4461 | 0.3979 | 0.4207 | 0.9497 |
| 115.5124 | 8.7324 | 15000 | 121.0585 | 0.4417 | 0.3949 | 0.4170 | 0.9496 |
| 114.7533 | 9.0234 | 15500 | 120.8895 | 0.4293 | 0.3940 | 0.4109 | 0.9493 |
| 114.7455 | 9.3145 | 16000 | 120.8019 | 0.4382 | 0.4048 | 0.4209 | 0.9495 |
| 114.2523 | 9.6056 | 16500 | 120.5313 | 0.4472 | 0.4083 | 0.4269 | 0.9503 |
| 114.6998 | 9.8967 | 17000 | 120.6184 | 0.4401 | 0.4037 | 0.4211 | 0.9497 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1
|
Solobrad/llama-3-8b-chat-doctor | Solobrad | "2024-09-26T05:04:06Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T05:02:30Z" | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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luaqi/nas52146578 | luaqi | "2024-09-26T05:03:37Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T05:03:37Z" | Entry not found |
kanhatakeyama/Tanuki-8B-dpo-v1.0-twitter-lora-r128-exp1 | kanhatakeyama | "2024-10-04T01:00:05Z" | 0 | 1 | transformers | [
"transformers",
"safetensors",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T05:03:39Z" | ---
library_name: transformers
license: apache-2.0
---
# Tanuki-8B-dpo-v1.0-twitter-lora-r128-exp1
- Tanuki-8B-dpo-v1.0-をチャット特化させるための試験バージョンです。
# original model
- [Tanuki-8B-dpo-v1.0-](https://huggingface.co/weblab-GENIAC/Tanuki-8B-dpo-v1.0)
# code
~~~
import transformers
#load model
model_id="weblab-GENIAC/Tanuki-8B-dpo-v1.0"
adapter_id="kanhatakeyama/Tanuki-8B-dpo-v1.0-twitter-lora-r128-exp1"
model=transformers.AutoModelForCausalLM.from_pretrained(model_id,trust_remote_code=True)
tokenizer=transformers.AutoTokenizer.from_pretrained(model_id,)
model.load_adapter(adapter_id)
#talk
pipe=transformers.pipeline("text-generation",model=model,tokenizer=tokenizer)
messages=[
{"role":"user","content":"元気???"},
]
prompt = pipe.tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=1024,
temperature=0.7,
repetition_penalty=1.1,
)
out_text = outputs[0]["generated_text"].lstrip(prompt)
print(out_text)
#うん!元気だよ〜😊あなたはどう?
~~~
### Training Data
- [kanhatakeyama/multiturn-conv-from-aozora-bunko](https://huggingface.co/datasets/kanhatakeyama/multiturn-conv-from-aozora-bunko)
- [kanhatakeyama/twitter-auto_reply (currently private dataset)](https://huggingface.co/datasets/kanhatakeyama/twitter-auto_reply)
- [kanhatakeyama/ramdom-to-fixed-multiturn-Calm3](https://huggingface.co/datasets/kanhatakeyama/ramdom-to-fixed-multiturn-Calm3) |
Akchacha/Qwen-Qwen1.5-1.8B-1727327026 | Akchacha | "2024-09-26T05:03:51Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:03:46Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
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## Model Details
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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SALUTEASD/Qwen-Qwen1.5-0.5B-1727327049 | SALUTEASD | "2024-09-26T05:04:09Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T05:04:09Z" | Entry not found |
smeby/Qwen-Qwen1.5-1.8B-1727327097 | smeby | "2024-09-26T05:04:59Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:04:57Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
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## Model Details
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saqqdy/Qwen-Qwen1.5-0.5B-1727327118 | saqqdy | "2024-09-26T05:05:21Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:05:18Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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dogssss/Qwen-Qwen1.5-0.5B-1727327123 | dogssss | "2024-09-26T05:05:27Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:05:23Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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[More Information Needed]
## Training Details
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jerseyjerry/Qwen-Qwen2-1.5B-Instruct-1727327140 | jerseyjerry | "2024-09-26T05:05:45Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen2-1.5B-Instruct",
"base_model:adapter:Qwen/Qwen2-1.5B-Instruct",
"region:us"
] | null | "2024-09-26T05:05:40Z" | ---
base_model: Qwen/Qwen2-1.5B-Instruct
library_name: peft
---
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Radmir-Gabidullin/Demi-Lovato | Radmir-Gabidullin | "2024-09-26T05:10:29Z" | 0 | 0 | null | [
"license:openrail",
"region:us"
] | null | "2024-09-26T05:06:01Z" | ---
license: openrail
---
|
Khoa/sentiment-analysis-tuning-golden-gate-0924-1 | Khoa | "2024-09-26T05:06:41Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"xlm-roberta",
"feature-extraction",
"arxiv:1910.09700",
"text-embeddings-inference",
"endpoints_compatible",
"region:us"
] | feature-extraction | "2024-09-26T05:06:18Z" | ---
library_name: transformers
tags: []
---
# Model Card for Model ID
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hamzaqureshi142/modsecurity-logs-CSV | hamzaqureshi142 | "2024-09-26T05:07:08Z" | 0 | 0 | null | [
"license:gpl-3.0",
"region:us"
] | null | "2024-09-26T05:07:08Z" | ---
license: gpl-3.0
---
|
SALUTEASD/Qwen-Qwen1.5-1.8B-1727327266 | SALUTEASD | "2024-09-26T05:07:52Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:07:46Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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xueyj/Qwen-Qwen1.5-1.8B-1727327346 | xueyj | "2024-09-26T05:09:13Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:09:07Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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xueyj/google-gemma-2b-1727327363 | xueyj | "2024-09-26T05:09:39Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T05:09:23Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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bagassi/nathaannew | bagassi | "2024-09-26T12:52:39Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T05:09:59Z" | Entry not found |
xueyj/Qwen-Qwen1.5-1.8B-1727327427 | xueyj | "2024-09-26T05:10:33Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:10:27Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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dogssss/Qwen-Qwen1.5-1.8B-1727327433 | dogssss | "2024-09-26T05:10:38Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:10:34Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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jerseyjerry/Qwen-Qwen1.5-1.8B-1727327443 | jerseyjerry | "2024-09-26T05:10:48Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:10:43Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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GraydientPlatformAPI/loras-sept26 | GraydientPlatformAPI | "2024-09-28T03:42:23Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T05:10:48Z" | Entry not found |
smeby/Qwen-Qwen1.5-0.5B-1727327488 | smeby | "2024-09-26T05:11:30Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:11:28Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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aiisa/Tradey | aiisa | "2024-09-26T05:11:51Z" | 0 | 0 | null | [
"license:mit",
"region:us"
] | null | "2024-09-26T05:11:51Z" | ---
license: mit
---
|
Krabat/Qwen-Qwen1.5-0.5B-1727327525 | Krabat | "2024-09-26T05:12:07Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:12:05Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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dalau627/text-to-sql-finetuned-mistral-small-2409-lora | dalau627 | "2024-09-30T23:39:19Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T05:12:23Z" | ---
library_name: transformers
tags: []
---
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xueyj/google-gemma-2b-1727327634 | xueyj | "2024-09-26T05:14:13Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T05:13:54Z" | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]
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### Framework versions
- PEFT 0.12.0 |
Luongdzung/oLora_500_last_question_wikiqa_without_label | Luongdzung | "2024-09-26T05:14:18Z" | 0 | 0 | peft | [
"peft",
"tensorboard",
"safetensors",
"generated_from_trainer",
"base_model:vlsp-2023-vllm/hoa-1b4",
"base_model:adapter:vlsp-2023-vllm/hoa-1b4",
"license:bigscience-bloom-rail-1.0",
"region:us"
] | null | "2024-09-26T05:14:14Z" | ---
base_model: vlsp-2023-vllm/hoa-1b4
library_name: peft
license: bigscience-bloom-rail-1.0
tags:
- generated_from_trainer
model-index:
- name: oLora_500_last_question_wikiqa_without_label
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# oLora_500_last_question_wikiqa_without_label
This model is a fine-tuned version of [vlsp-2023-vllm/hoa-1b4](https://huggingface.co/vlsp-2023-vllm/hoa-1b4) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3835
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3814 | 1.0 | 50 | 0.3930 |
| 0.4125 | 2.0 | 100 | 0.3835 |
| 0.3877 | 3.0 | 150 | 0.3859 |
### Framework versions
- PEFT 0.13.0
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1 |
xueyj/google-gemma-2b-1727327655 | xueyj | "2024-09-26T05:14:43Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T05:14:15Z" | ---
base_model: google/gemma-2b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
[More Information Needed]
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
#### Preprocessing [optional]
[More Information Needed]
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#### Speeds, Sizes, Times [optional]
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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## Evaluation
<!-- This section describes the evaluation protocols and provides the results. -->
### Testing Data, Factors & Metrics
#### Testing Data
<!-- This should link to a Dataset Card if possible. -->
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#### Metrics
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
### Compute Infrastructure
[More Information Needed]
#### Hardware
[More Information Needed]
#### Software
[More Information Needed]
## Citation [optional]
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**BibTeX:**
[More Information Needed]
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[More Information Needed]
## Glossary [optional]
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
[More Information Needed]
## More Information [optional]
[More Information Needed]
## Model Card Authors [optional]
[More Information Needed]
## Model Card Contact
[More Information Needed]
### Framework versions
- PEFT 0.12.0 |
agamgoy/llama-3-task-2-group-Education_and_Learning | agamgoy | "2024-09-26T05:14:31Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"base_model:unsloth/llama-3-8b-bnb-4bit",
"base_model:finetune:unsloth/llama-3-8b-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T05:14:24Z" | ---
base_model: unsloth/llama-3-8b-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
---
# Uploaded model
- **Developed by:** agamgoy
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
vietphuon/Llama-3.2-1B-Instruct-bnb-4bit-240926-1 | vietphuon | "2024-09-26T08:02:02Z" | 0 | 0 | transformers | [
"transformers",
"safetensors",
"text-generation-inference",
"unsloth",
"llama",
"trl",
"en",
"dataset:yahma/alpaca-cleaned",
"base_model:unsloth/Llama-3.2-1B-Instruct-bnb-4bit",
"base_model:finetune:unsloth/Llama-3.2-1B-Instruct-bnb-4bit",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | "2024-09-26T05:14:54Z" | ---
base_model: unsloth/Llama-3.2-1B-Instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
datasets:
- yahma/alpaca-cleaned
---
# Description
- **Motivation:** Fine-tuned version of Llama 3.2 model to generate a quiz for a given context. This version is just poorly trained on the Alpaca version (Chatbot usecase). Also this dataset only have 80 data points on json task [https://huggingface.co/datasets/yahma/alpaca-cleaned/viewer/default/train?q=json] so the model also weak on structured json output.
# Uploaded model
- **Developed by:** vietphuon
- **License:** apache-2.0
- **Finetuned from model :** unsloth/Llama-3.2-1B-Instruct-bnb-4bit
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
dogssss/Qwen-Qwen1.5-0.5B-1727327713 | dogssss | "2024-09-26T05:15:18Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:15:14Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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[More Information Needed]
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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### Framework versions
- PEFT 0.12.0 |
SALUTEASD/Qwen-Qwen1.5-1.8B-1727327831 | SALUTEASD | "2024-09-26T05:17:16Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:17:11Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
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- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
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[More Information Needed]
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[More Information Needed]
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
[More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
[More Information Needed]
## Training Details
### Training Data
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[More Information Needed]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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### Testing Data, Factors & Metrics
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<!-- This should link to a Dataset Card if possible. -->
[More Information Needed]
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
[More Information Needed]
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[More Information Needed]
### Results
[More Information Needed]
#### Summary
## Model Examination [optional]
<!-- Relevant interpretability work for the model goes here -->
[More Information Needed]
## Environmental Impact
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
- **Hardware Type:** [More Information Needed]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
- **Compute Region:** [More Information Needed]
- **Carbon Emitted:** [More Information Needed]
## Technical Specifications [optional]
### Model Architecture and Objective
[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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[More Information Needed]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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### Framework versions
- PEFT 0.12.0 |
xueyj/google-gemma-7b-1727327842 | xueyj | "2024-09-26T05:17:36Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-7b",
"base_model:adapter:google/gemma-7b",
"region:us"
] | null | "2024-09-26T05:17:22Z" | ---
base_model: google/gemma-7b
library_name: peft
---
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
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- **License:** [More Information Needed]
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### Model Sources [optional]
<!-- Provide the basic links for the model. -->
- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
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### Out-of-Scope Use
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saqqdy/Qwen-Qwen1.5-0.5B-1727327858 | saqqdy | "2024-09-26T05:17:42Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:17:39Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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feelsogoodeasy/Qwen-Qwen1.5-0.5B-1727327912 | feelsogoodeasy | "2024-09-26T05:18:38Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:18:33Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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xueyj/Qwen-Qwen1.5-0.5B-1727327936 | xueyj | "2024-09-26T05:19:03Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:18:56Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
# Model Card for Model ID
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Hieu-Hien/mulgat-bart-base-ed-8000 | Hieu-Hien | "2024-09-26T05:21:02Z" | 0 | 0 | null | [
"safetensors",
"bart",
"region:us"
] | null | "2024-09-26T05:19:08Z" | Entry not found |
terry69/preference_p0.1_seed42_level2_syntaxmixbatch16_reverse | terry69 | "2024-09-26T05:19:19Z" | 0 | 0 | null | [
"region:us"
] | null | "2024-09-26T05:19:19Z" | Entry not found |
jerseyjerry/google-gemma-2b-it-1727327991 | jerseyjerry | "2024-09-26T05:19:59Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b-it",
"base_model:adapter:google/gemma-2b-it",
"region:us"
] | null | "2024-09-26T05:19:51Z" | ---
base_model: google/gemma-2b-it
library_name: peft
---
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SALUTEASD/google-gemma-2b-1727327991 | SALUTEASD | "2024-09-26T05:20:18Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:google/gemma-2b",
"base_model:adapter:google/gemma-2b",
"region:us"
] | null | "2024-09-26T05:19:52Z" | ---
base_model: google/gemma-2b
library_name: peft
---
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xueyj/Qwen-Qwen1.5-0.5B-1727327999 | xueyj | "2024-09-26T05:22:24Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:20:00Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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dogssss/Qwen-Qwen1.5-1.8B-1727328023 | dogssss | "2024-09-26T05:20:26Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:20:24Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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xueyj/Qwen-Qwen1.5-0.5B-1727328025 | xueyj | "2024-09-26T05:20:31Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:20:25Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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feelsogoodeasy/Qwen-Qwen1.5-1.8B-1727328044 | feelsogoodeasy | "2024-09-26T05:20:51Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:20:45Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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Adidacta/adidush | Adidacta | "2024-09-26T07:36:43Z" | 0 | 0 | null | [
"license:other",
"region:us"
] | null | "2024-09-26T05:21:03Z" | ---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
--- |
xueyj/Qwen-Qwen1.5-1.8B-1727328081 | xueyj | "2024-09-26T05:21:27Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-1.8B",
"base_model:adapter:Qwen/Qwen1.5-1.8B",
"region:us"
] | null | "2024-09-26T05:21:21Z" | ---
base_model: Qwen/Qwen1.5-1.8B
library_name: peft
---
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DAKPLUTO/Qwen-Qwen1.5-0.5B-1727328159 | DAKPLUTO | "2024-09-26T05:22:41Z" | 0 | 0 | peft | [
"peft",
"safetensors",
"arxiv:1910.09700",
"base_model:Qwen/Qwen1.5-0.5B",
"base_model:adapter:Qwen/Qwen1.5-0.5B",
"region:us"
] | null | "2024-09-26T05:22:38Z" | ---
base_model: Qwen/Qwen1.5-0.5B
library_name: peft
---
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## Uses
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### Direct Use
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### Downstream Use [optional]
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### Out-of-Scope Use
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## Bias, Risks, and Limitations
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### Recommendations
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
## How to Get Started with the Model
Use the code below to get started with the model.
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## Training Details
### Training Data
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### Training Procedure
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#### Preprocessing [optional]
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#### Training Hyperparameters
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## Evaluation
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### Testing Data, Factors & Metrics
#### Testing Data
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#### Factors
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#### Metrics
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### Results
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#### Summary
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## Environmental Impact
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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## Technical Specifications [optional]
### Model Architecture and Objective
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## Citation [optional]
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## Glossary [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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### Framework versions
- PEFT 0.12.0 |