|
--- |
|
library_name: transformers |
|
datasets: |
|
- allenai/c4 |
|
--- |
|
|
|
# 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. --> |
|
|
|
This model is a quantized version of Falcon2-11B by [tiiuae](https://huggingface.co/tiiuae/falcon-11B). Quantization was performed with Auto-GPTQ to 2bit. |
|
|
|
- **Developed by:** TIIIUAE |
|
- **Quantised by:** Michael Svendsen |
|
|
|
### Getting Started |
|
```python |
|
from transformers import AutoTokenizer, AutoModelForCausalLM, GPTQConfig |
|
|
|
pretrained_model_name = "thesven/falcon-11B-GPTQ-2bit" |
|
device = "cuda:0" |
|
|
|
# Load the tokenizer |
|
tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name) |
|
|
|
# Load the model with the specified configuration and move to device |
|
model = AutoModelForCausalLM.from_pretrained( |
|
pretrained_model_name, |
|
device_map="auto", |
|
) |
|
# Set EOS token ID |
|
model.eos_token_id = tokenizer.eos_token_id |
|
|
|
# Move model to the specified device |
|
model.to(device) |
|
|
|
# Define the input text |
|
input_text = "Why is the sky blue?" |
|
|
|
# Encode the input text |
|
input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device) |
|
|
|
# Generate output |
|
output = model.generate(input_ids, max_length=1000) |
|
|
|
# Decode the generated output |
|
decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True) |
|
|
|
# Print the decoded output |
|
for i, sequence in enumerate(decoded_output): |
|
print(f"Generated Sequence {i+1}: {sequence}") |
|
|
|
|
|
``` |
|
|
|
## License |
|
Falcon2-11B is licenced under [TII Falcon License 2.0(https://falconllm-staging.tii.ae/falcon-2-terms-and-conditions.html), the permissive Apache 2.0-based software license which includes an acceptable use policy that promotes the responsible use of AI. |
|
|
|
|
|
## Uses |
|
### Direct Use |
|
Research on large language models; as a foundation for further specialization and finetuning for specific usecases (e.g., summarization, text generation, chatbot, etc.) |
|
|
|
### Out-of-Scope Use |
|
Production use without adequate assessment of risks and mitigation; any use cases which may be considered irresponsible or harmful. |
|
|
|
### Bias, Risks, and Limitations |
|
Falcon2-11B is trained mostly on English, but also German, Spanish, French, Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish. It will not generalize appropriately to other languages. Furthermore, as it is trained on a large-scale corpora representative of the web, it will carry the stereotypes and biases commonly encountered online. |
|
|
|
### Recommendations |
|
We recommend users of Falcon2-11B to consider finetuning it for the specific set of tasks of interest, and for guardrails and appropriate precautions to be taken for any production use. |
